dissertation final - Gradworks

Transcription

THE EFFECTS OF AN INTERDISCIPLINARY UNDERGRADUATE HUMAN
BIOLOGY PROGRAM ON SOCIOSCIENTIFIC REASONING, CONTENT
LEARNING, AND UNDERSTANDING OF INQUIRY
Jennifer L. Eastwood
Submitted to the faculty of the University Graduate School in partial fulfillment of the
requirements for the degree Doctor of Philosophy in the Department of Curriculum and Instruction,
Indiana University, August 2010
UMI Number: 3423606
All rights reserved
INFORMATION TO ALL USERS
The quality of this reproduction is dependent upon the quality of the copy submitted.
In the unlikely event that the author did not send a complete manuscript
and there are missing pages, these will be noted. Also, if material had to be removed,
a note will indicate the deletion.
UMI 3423606
Copyright 2010 by ProQuest LLC.
All rights reserved. This edition of the work is protected against
unauthorized copying under Title 17, United States Code.
ProQuest LLC
789 East Eisenhower Parkway
P.O. Box 1346
Ann Arbor, MI 48106-1346
Accepted by the Graduate Faculty, Indiana University, in partial fulfillment of the requirements
for the degree of Doctor of Philosophy.
Doctoral Committee
_______________________________________
Robert D. Sherwood, Ph.D.
_______________________________________
Valarie Akerson, Ph.D.
_______________________________________
Meredith Park Rogers, Ph.D.
_______________________________________
Whitney M. Schlegel, Ph.D.
May 10, 2010
ii © 2010
Jennifer L. Eastwood
ALL RIGHTS RESERVED
iii Acknowledgments
I would like to thank my dissertation committee for their encouragement and guidance
throughout this project. I am grateful to my advisor, Dr. Bob Sherwood, for giving careful
feedback that strengthened my work. He always expressed confidence in me, which helped me to
persist on the dissertation. I would like to thank Dr. Whitney Schlegel for sharing her passion for
improving college science education and her creativity with the development of the Human
Biology Program. I am grateful to have had the opportunity to work with Human Biology as well
as to grow through sharing ideas with her over coffee. I would like to thank Dr. Valarie Akerson
and Dr. Meredith Park Rogers for their feedback on my proposal, which helped me to design a
better study, and their insightful comments on the dissertation, which will help guide my future
research. I am grateful to all the Science Education faculty for their investment in me though
teaching and research projects, which has helped me to learn the field. I would also like to thank
Kristin Cook, Vanashri Nargund , and Cathy Smith who each provided special contributions to
my project.
Most of all, I would like to thank my family for supporting me throughout my entire
degree. To my husband Bill, thank you for the countless times you put your work on hold so I
could finish my dissertation! And thank you for not complaining when I rehashed my outline to
you over and over. I could not have finished my degree without your support, flexibility, and
wonderful care of our daughter. Thank you to Ashleigh for being a Science Ed kid and thank you
to Andrew for arriving just on time for me to finish the defense! I love you all and thank you for
inspiring me to finish my degree.
iv Jennifer L. Eastwood
The Effects of an Interdisciplinary Undergraduate Human Biology Program on Socioscientific Reasoning,
Content Learning, and Understanding of Inquiry
Preparing students to take informed positions on complex problems through critical evaluation is a primary
goal of university education. Socioscientific issues (SSI) have been established as effective contexts for
students to develop this competency, as well as reasoning skills and content knowledge. This mixedmethods study investigates the effects of an interdisciplinary undergraduate human biology program
focused on the development of evidence-based reasoning to form personal commitments on SSI.
Specifically, the study investigates how human biology majors differ from traditional biology majors in
their reasoning with SSI, their perceptions of experiences with SSI, their understanding of scientific
inquiry, their levels and perceptions of science content knowledge, and their general program perceptions.
These outcomes were assessed through open-ended questionnaires on SSI and scientific inquiry and a basic
biology concept test administered to 95 participants representing both programs and 16 semi-structured
student interviews. Although the two groups did not differ significantly in their decisions or factors
influencing their decisions in SSI, human biology majors showed higher levels of socioscientific reasoning,
suggesting that learning contextualized in SSI helped them understand and reason with similar issues.
While biology majors reported few experiences with socioscientific reasoning, human biology majors felt
well equipped to reason with SSI and more likely to consider alternative perspectives in their decision
making. Human biology majors also were more likely to view social science research as a form of inquiry
and less likely to view scientific inquiry as purely experimental. No difference was found between groups
in basic biology content knowledge, although human biology majors felt they were exposed to less detailed
biology content. This exploratory study illustrates a novel approach to interdisciplinary, SSI-based science
education at the college level.
__________________________________________________
__________________________________________________
__________________________________________________
__________________________________________________
v TABLE OF CONTENTS
Page
ACCEPTANCE PAGE
ii
COPYRIGHT PAGE
iii
ACKNOWLEDGMENTS
iv
ABSTRACT OF THE DISSERTATION
v
LIST OF TABLES AND FIGURES
x
CHAPTER 1: Introduction
1
Rationale
1
Motivation for Research
3
Research Questions
5
CHAPTER 2: Background for Study
8
Theoretical Framework
8
Situated Cognition
8
Developmental Constructs in College Students
8
Literature Review
13
Socioscientific Issues
13
Interdisciplinary Learning
21
Collaborative Learning
27
Contextualized Learning
34
Relation to Study
43
CHAPTER 3: Method
45
Context of Study
45
SSI Group
45
Biology Comparison Group
55
vi Methodology
56
Worldview
56
Research Design
57
Participants
57
General Procedures of Data Collection
61
Data Collection for Reasoning and Perceptions of SSI
63
Data Analysis for Reasoning and Perceptions of SSI
64
Data Collection for Understanding of Scientific Inquiry
70
Data Analysis for Understanding of Scientific Inquiry
72
Data Collection for Levels and Perceptions of Biology
Content Knowledge
73
Data Analysis of Levels and Perceptions of Content
Knowledge
74
Data Collection for General Perceptions of Major
75
Summary of Methods
76
CHAPTER 4: Results
77
Socioscientific Reasoning and Perceptions of SSI
77
Comparison of Decisions
77
Comparison of Factors Influencing Reasoning
78
Comparison of Reasoning
82
Comparison of Reasoning in DMQ Follow-up Questions
83
Perceptions of SSI in Majors
84
Understanding of Inquiry
89
Modified Views of Scientific Inquiry Questionnaire
89
Inquiry Portion of Interviews
102
vii Levels and Perceptions of Biology Content Knowledge
106
Biology Concept Inventory
106
Perceptions of Biology Content Knowledge Portion of
Interview
107
Student Perceptions of Majors
110
Perceptions of Personal Outcomes
110
Perceptions of the Learning Environment
113
CHAPTER 5: Discussion
117
Review of Study
118
118
Socioscientific Reasoning
118
Consideration of Multiple Perspectives
122
Understanding of Scientific Inquiry
124
Views of Different Disciplines and Perspectives in
Science
124
Views of the Scientific Method and Experiment
126
Data and Evidence
129
Tentativeness of Theory and Purpose of Theory
130
Levels and Perceptions of Biology Content Knowledge
131
Perceptions of Majors
133
133
136
Limitations of the Study
137
Major Findings and Implications
140
Future Directions
142
viii Conclusion
143
REFERENCES
145
APPENDIX A: Informed Consent Statement
152
APPENDIX B: Overhead Slide for Participant Recruitment
154
APPENDIX C: Demographic Sheet
155
APPENDIX D: Open-ended Questionnaire
157
APPENDIX E: Biology Concept Inventory
162
APPENDIX F: Semistructured Interview Protocol for Human Biology
and Biology Majors
170
APPENDIX G: Coding Scheme for the Modified VOSI
172
APPENDIX H: Methods Matrix
178
CURRICULUM VITA
180
ix LIST OF TABLES AND FIGURES
Page
Table 1. Demographic information for SSI and BIO participants.
60
Table 2. Rubric for reasoning and perspectives applied to DMQ
66
Table 3. Examples of scoring for reasoning scale.
67
Table 4. Examples of scoring for perspectives scale
68
Table 5. Assessment themes for stages of reflective judgment
70
Table 6. Percentages of SSI and BIO students by decision for questions
on the modified DMQ
78
Table 7. Factors influencing reasoning in Climate change and policy
question cluster of DMQ
80
Table 8. Factors influencing reasoning in Diet and health research/food
choice question cluster of DMQ
80
Table 9. Factors influencing reasoning in Regulation of food or tobacco
question cluster of DMQ
81
Table 10. Reasoning scores for SSI and BIO groups
82
Table 11. Perspectives scores for SSI and BIO groups
83
Table 12. Codes for VOSI Question 1
90
91
Table 14. Codes for VOSI Question 3a
92
Table 15. Codes for VOSI Question 3b
92
Table 16. Codes for VOSI Question 3c
93
94
94
Table 19. Codes for VOSI Question 4c
95
x Table 20. Codes for VOSI Question 5a
96
97
98
99
100
101
Table 26. BCI scores for SSI and BIO groups
107
Figure 1. Convergence model of triangulation design for dissertation
76, 118
xi CHAPTER 1: INTRODUCTION
Rationale
Preparing students to take informed positions on complex problems through
critical evaluation is considered a primary goal of university education (Association of
American Colleges and Universities, 2007; King & Kitchener, 1994; Baxter Magolda,
1999) and an important aspect of scientific literacy (Sadler & Zeidler, 2009; Roberts,
2007). In approaching contemporary problems, the ability to understand and position
oneself in interdisciplinary issues is essential (Boix Mansilla & Duraising, 2007). This is
especially true where the study of biology meets contemporary global problems. For
example, to understand the nature of disease, it is essential to examine psychological and
socioeconomic aspects as well as biology and pathology. Even when such socioscientific
issues have been addressed in the classroom, however, studies have found that instruction
has focused on subject matter knowledge, giving little attention to the importance of
informed decision making (Lederman, 2003). In recent literature, the pedagogical
framework of socioscientific issues (SSI), which integrates science concepts and their
social significance, involving students in a community of dialogue, discussion, and
debate, has been established as effective for students to develop their reasoning with the
types of issues described, as well as content knowledge (Sadler, 2009; Zeidler, Sadler,
Applebaum, & Callahan, 2009).
The national initiative, Science for All Americans, calls for science education that
promotes decision making for citizenship (Rutherford and Ahlgren, 1991). Consistent
with this goal, a recent report of the Association of American Colleges and Universities
(2007) asserts
1 The LEAP [Liberal Education and America’s Promise] National
Leadership Council recommends, in sum, an education that intentionally
fosters, across multiple fields of study, wide-ranging knowledge of
science, cultures, and society; high-level intellectual and practical skills;
an active commitment to personal and social responsibility; and the
demonstrated ability to apply learning to complex problems and
challenges (p. 4).
The goals of the SSI movement overlap significantly with those of university
educators to help students learn to integrate disciplines to responsibly approach real
problems. Much of the literature on SSI has concentrated on decision making for
citizenship, however, fluency in discussing socioscientific issues and integrating
perspectives from different disciplinary fields will be especially important for those
entering fields that will tackle problems like climate change and epidemics (Thompson
Klein, 1990). The Institute of Medicine (IOM) has recognized a need for goals consistent
with those of SSI in the training of physicians. The IOM calls for integration of the social
sciences in medical curricula, considering half of the mortality in the US can be attributed
to social factors, including diet, drug abuse, and lifestyle habits (2004). According to the
IOM, “To make measurable improvements in the health of Americans, physicians must
be equipped with the knowledge and skills from the behavioral and social sciences
needed to recognize, understand, and effectively respond to patients as individuals, not
just to their symptoms” (p. 16). Extending these goals to undergraduate science majors
who will enter medical school and health careers, more research is needed into effective
learning contexts for developing socioscientific reasoning and integration of different
perspectives into decision making.
In addition to the gap in the literature describing SSI as preparation for science
careers, most studies of SSI contexts have focused on K-12 students, but few have been
2 conducted with adults or college students (Bell & Lederman, 2003). Since many
researchers have documented important changes in cognitive and ethical development, as
well as reasoning approaches (Baxter Magolda, 1999; King & Kitchener, 1994, Perry,
1970), outcomes of SSI in college students are likely to differ from those of younger
students. Also, very few studies have investigated SSI interventions spanning more than a
unit or semester (Zeidler et al., 2009). This study addresses these gaps in the literature.
Motivation for Research
My interest in this research developed from my experiences as a student and
instructor in college level biology courses. Reflecting on the very structured labs I taught
and the courses I took as an undergraduate, I questioned the effectiveness of the
predominant lecture-based approach in traditional biology courses. I began to read about
student centered and active learning approaches such as case-based and collaborative
learning, as well as SSI, which incorporates both of these approaches. As a student in
science education, I became familiar with research studies documenting the success and
conditions for these teaching strategies, observed courses employing them, and
incorporated them into my own teaching. These experiences convinced me that students
gain knowledge that is more meaningful to them and more transferrable to new situations
when they have opportunities to discuss and explain concepts to peers and apply concepts
to real problems.
Through pre-dissertation research and in-depth discussion with a mentor who is
an expert in biology education and physiology professor, I explored the outcomes and
conditions necessary for effective case-based and team-based biology instruction. This
experience impressed me because students increased their content knowledge by working
3 together and anecdotally reported deeper and longer-lasting understanding of the content
as compared to their other biology courses, but expressed extreme frustration with team
work. I was convinced that situated and collaborative learning were highly effective in
teaching science content, but they were also difficult to employ successfully since they
deviated from students’ expectations and comfort levels.
In addition, the biology professor I worked with introduced me to literature on
cognitive and ethical development in college students. Through reading and discussing
the work of Perry (1979) and Baxter Magolda (1994), I was convinced that college
students exhibit consistent patterns in their understanding of knowledge and approaches
to learning as they develop in a college environment. Understanding these patterns can
help instructors to grasp how their students are thinking and begin instruction from what
their students know. Understanding these patterns helps instructors scaffold their
students. It also helps instructors articulate desired outcomes for students, such as
understanding knowledge as a product of human inquiry rather than mandated facts to
memorize.
I became interested in the Human Biology program, since the program director
(also the biology professor who had mentored me) and faculty had carefully designed the
program to enact the strategies I have discussed and reflect a theoretical position based on
developmental research. The program used an interdisciplinary approach to help students
learn to reason and take positions on controversial issues with both scientific and social
implications. I saw the goals of the program and the pedagogical strategies employed as
consistent with SSI, and felt that description of Human Biology core courses could
contribute to the SSI literature by illustrating how SSI was taught and how students
4 responded within a college level learning environment. Based on my experience and prior
knowledge, I approached this study with a personal bias toward the Human Biology
program. Since the program goals, pedagogical strategies, and curricula were consistent
with effective practices from the literature, I expected Human Biology students to have
better learning gains and epistemological development than students in a traditional
biology major.
However, I recognized the complexity of the learning environment where many
approaches are integrated and imperfectly employed. Key aspects of the Human Biology
program, including collaboration, situated learning, and reflective practice have shown
various levels of effectiveness in prior research considering that outcomes are affected by
countless variables. Although I expected better outcomes for students in Human Biology,
I approached the learning environment hoping to uncover specific aspects of both majors
that helped or hindered learning through interviews, open-ended questionnaires, and
observation. Considering my prior expectations that the pedagogy of the Human Biology
program would result in better outcomes, I attempted to limit my own bias through blind
analysis of questionnaires, semi-structured interview protocols, and consultation with
other researchers on both instruments and collected data. I recognize, however, that my
desire to find evidence supporting the SSI-based approach in Human Biology is a
limitation of the study.
Research Questions
My dissertation investigates the effects of a four-year interdisciplinary
undergraduate Human Biology program focused on the progressive development of
evidence-based reasoning skills and reflective judgment to form personal commitments
5 on real interdisciplinary issues. Although the program incorporates many theoretical
constructs and pedagogical strategies, I will focus on the SSI context embodied in the
program. As Human Biology students typically chose the program as an alternative to the
traditional biology major and are similar in achievement and future career paths, my
dissertation compares Human Biology and biology majors. I first address how Human
Biology majors compared with traditional biology majors in reasoning and experiences
with SSI. I then address how the context of the program affected students’ understanding
of scientific inquiry. Scientific inquiry is explicitly discussed and practiced throughout
the Human Biology program as a means of providing evidence-based conclusions about
scientific phenomena, and is a central disciplinary process in science. Thirdly I address
how levels and perceptions of biology content knowledge differ between groups,
exploring the criticism that Human Biology majors may compromise basic science
knowledge in their focus on interdisciplinary, socioscientific issues. Finally, I compare
general perceptions of biology and Human Biology majors, including perceptions of
outcomes and perceptions of the learning environment. Research questions include:
(1) Do Human Biology majors reason with SSI differently from traditional biology
majors?
(2) How do Human Biology and traditional biology majors’ perceptions of their
experiences with SSI differ?
(3) Do Human Biology and biology majors understand scientific inquiry differently?
6 Levels and Perceptions of Biology Content Knowledge
(4) Do Human Biology and biology majors differ in their general biology content
knowledge?
(5) How do Human Biology and traditional biology majors’ perceptions of their content
knowledge differ?
General Perceptions of Majors
(6) How do Human Biology and traditional biology majors’ general perceptions of their
majors differ?
7 CHAPTER TWO: BACKGROUND FOR STUDY
Theoretical Framework
In my dissertation research, I view student development through a theoretical lens
informed by situated cognition and the complementary developmental theories of King
and Kitchener (1994), Perry (1999), and Baxter Magolda (1992, 1999).
Situated Cognition
My theoretical lens is informed by situated cognition, which posits that
knowledge is connected to the context in which it is learned (Brown et al., 1989). As a
tool is understood through its use, students make sense of a new concept in the context of
its application and discipline. Domain-specific learning promotes a knowledge structure
that allows knowledge to be accessed for relevant problems and not remain “inert”
(Bransford et al., 1986). Effective learning environments offer students opportunities to
work with and apply concepts in contexts authentic to their use. They also remain
authentic to common practices in the fields, such as collaboration. For example,
physicians, nurses, and other health care professionals work in teams, and scientists
collaborate among and between research teams. Through this theoretical lens, pedagogy
that emphasizes interpersonal interaction and is contextualized in realistic problems
should promote development of concepts, skills, and disciplinary knowledge.
Developmental Constructs in College Students
Reflective Judgment
Based on their longitudinal study with college students, King and Kitchener
(1994) assert that reflective thinking is needed in uncertain or controversial situations. To
manage situations where information is incomplete, people need to continually evaluate
8 tentative solutions in terms of usefulness and plausibility, incorporating new data and
different arguments. The Reflective Judgment Model describes a pattern of development
of “epistemic cognition:” “As individuals develop, they become better able to evaluate
knowledge claims and to explain and defend their points of view on controversial issues”
(King & Kitchener, 1994, p. 13).
As developmental theorists, King and Kitchener (1994) identified patterns or
stages of development through which individuals progress. The first three stages are prereflective, where knowledge is viewed as absolute, concrete, and directly observable,
though sometimes unavailable or temporarily uncertain. Pre-reflective thinkers see direct
correspondence between their beliefs and truth or assertions of authority and truth.
Alternate positions are not perceived and there is no conflict because “right” answers
clearly exist.
The middle two developmental stages are quasi-reflective. Knowledge is viewed
as either uncertain or contextual, and knowledge claims tend to be idiosyncratic, for
example only evidence supporting a belief may be considered. Quasi-reflective thinkers
may see beliefs as tied to context, where alternative beliefs with different contexts are
viewed as equally true. Quasi-reflective thinkers may be hindered by complexity in
forming conclusions (King & Kitchener, 1994).
The last two stages are the reflective stages. Reflective thinkers recognize
knowledge as an outcome of inquiry and originating from different sources. Knowledge
claims are evaluated based on evidence. Ideas are considered across contexts and
different perspectives are perceived and incorporated into reasoning. Criteria such as
9 weight of evidence, and need for and usefulness of a solution are applied in reasoning
(King & Kitchener, 1994).
Perry’s Scheme of Intellectual and Ethical Development
Through interview data from a fifteen year study with Harvard undergraduates,
Perry developed a model for the ways students view their experiences throughout their
college years. Students tend to enter college from the perspective of simple dualism,
where knowledge is seen as dualistic (right versus wrong, good versus bad), and right
answers are held by authorities. In complex dualism, uncertainty and differing opinions
are acknowledged, but seen as results of poorly informed authorities or undiscovered
answers. In relativism, students accept differing positions as personal opinions and view
values and knowledge as contextual. In the most mature positions, termed commitment in
relativism, students recognize multiple views, but develop and act upon a commitment to
a particular view (Perry, 1999). Insights from Perry on how students view the nature of
knowledge shed light on how students perceive experiences with interdisciplinary and
SSI-based learning environments.
Epistemological Reflection Model
Baxter Magolda (1992) developed the Epistemological Reflection model through
a longitudinal study with eighty students through their college years and eight years postcollege. Her model relates to those of Perry and King and Kitchener, but also
incorporates gender-related patterns. She used open-ended interviews to probe
participants on their views of knowledge, learning, and influences of different aspects of
their educational experience. She identified four reasoning patterns.
10 First, absolute knowers, typically in the first two years of college, viewed
knowledge as right or wrong with no uncertainty. The instructor’s role is to
authoritatively convey knowledge and the learner’s role is to acquire that knowledge.
Female absolute knowers were more likely to exhibit a receiving pattern where
knowledge was gained by passively listening and taking notes, and male absolute
knowers were more likely to use a mastery pattern, actively seeking interaction with
instructors and peers.
In the second pattern, transitional knowing, seen throughout the college years,
individuals perceived uncertainty in some areas. For example, certainty remained in
chemistry, but uncertainty was understood in studying AIDS. In this stage, participants
moved from a focus on acquiring knowledge toward understanding, and required more
opportunities to explore ideas with others. Female transitional knowers tended to use an
interpersonal approach, desiring to hear perspectives of peers, express their own ideas on
uncertain issues with encouragement of instructors, and use personal judgment to resolve
uncertainty. Male transitional knowers tended to use an impersonal approach, where they
valued debate, fairness of evaluation, and resolving uncertainty through logic and
background research.
In the third pattern, independent knowing, seen toward the end and after college,
students perceived uncertainty and viewed ideas of peers as equally valid to those of
authority. Women more commonly espoused the interindividual pattern, where they
valued both listening to others’ views and developing their own, and used others’ views
to develop their own. Men more commonly espoused the individual pattern, where they
focused on their own ideas, but attempted to listen to others.
11 The fourth pattern, contextual knowing, emerged in students toward the end of
college or after college. Baxter Magolda says, “Contextual knowers looked at all aspects
of a situation or issue, sought out expert advice in that particular context, and integrated
their own and others’ views in deciding what to think.” (1999, p. 50). These individuals
integrated relational and impersonal, or individualized ways of knowing. They relied on
evidence from different sources to form their own positions.
Conception of Human Biology Program through Theoretical Framework
Through my theoretical lens, pedagogy that emphasizes interpersonal interaction
and is contextualized in realistic problems should promote development of concepts and
skills, and disciplinary knowledge. In the Human Biology program, case studies situate
learning in realistic problems, promoting development of knowledge less likely to remain
“inert.” The collaborative nature of the program promotes cognitive development through
interaction and explanation, and situates learning in a realistic context, since biological
inquiry is generally a collaborative endeavor. Through participation in inquiry, students
should gain an understanding of the inquiry process.
Aspects of Reflective Judgment (King & Kitchener, 1994) have been recognized
as important epistemic competencies for reasoning in SSI, such as recognizing problems
as complex and inquiry-based, considering multiple perspectives, and using evidence to
make decisions (Zeidler, Sadler, Applebaum, & Callahan, 2009). Complementary to this
framework, I view SSI, as enacted in the Human Biology program, as consistent with the
goals of interdisciplinary learning, to help students apply disciplinary lenses to
understand and take positions on complex problems (Thompson Klein, 1990; Boix
Mansilla, 2000).
12 The developmental frameworks discussed serve as theoretical foundations for my
study in understanding the epistemological assumptions behind student perceptions. My
goal is not to apply developmental stages to participants or document changes in their
developmental stages, but to approach my research with the understanding that the ability
to perceive complexity or uncertainty in situations, understand inquiry-based rather than
authority-based sources of knowledge, base personal positions on evidence, and consider
multiple perspectives develops over time. The classroom environment, including roles of
instructors and peers is important, and reasoning with such ill-structured problems may
facilitate these developmental processes (Baxter Magolda, 1992; Baxter Magolda, 1999;
Zeidler, Sadler, Applebaum, & Callahan, 2009).
Literature Review
This study examines Human Biology students’ understanding of socioscientific
issues, understanding of inquiry, and biology conceptual knowledge. The study examines
how key pedagogical aspects of the program including integration of disciplines, position
taking on socioscientific issues, collaboration, and contextualization of learning in
authentic activities relate to those outcomes and perceptions of those outcomes. In this
literature review, I discuss theory and research on these aspects of the program.
Socioscientific issues (SSI) are often centered in problems that may be informed
by concepts, theories, and methods from multiple disciplines. Many challenges
individuals and nations must face currently and in the near future, such as dilemmas
brought about by medical advances or environmental issues related to a growing human
population, may be addressed from perspectives from both biology and the social
13 sciences (Sadler, 2004). Sadler (2004) defines SSI as having “central roles of both social
and scientific factors.” Many proponents for including SSI in science curricula argue that
they promote development of students into citizens able to apply scientific knowledge
and “habits of mind” to decisions. (Sadler). The American Association for the
Advancement of Science (1990) and the National Research Council (1996) consider
ability to negotiate SSI an important part of scientific literacy. Sadler & Zeidler (2009)
explain how SSI is consistent with Roberts’ (2007) Vision II of scientific literacy, which
“derives its meaning from the character of situations with a scientific component,
situations that students are likely to encounter as citizens” (p. 730). Similarly, they view
SSI as consistent with the PISA definition of scientific literacy, including “scientific
knowledge and use of that knowledge to identify questions, to acquire new knowledge, to
explain scientific phenomena, and to draw evidence-based conclusions about sciencerelated issues,” science as an inquiry-based human endeavor of seeking knowledge,
awareness of the roles of science and technology in defining our physical, social and
cultural environments, and willingness to approach issues of science and technology
reflectively (Sadler & Zeidler, 2009).
The SSI movement builds upon the Science, Technology, and Society (STS)
movement, which emerged in the early 1980s. STS sought to help students understand
how the areas of science technology and social issues are interdependent, but according
to Sadler (2004), the SSI movement focuses on “empowering” students to make informed
decisions on science issues that impact and will impact their lives. Going beyond the
boundaries of STS, SSI take into consideration the ethical value of decisions and moral
development of students (Zeidler, Sadler, Simmons, & Howe, 2005). In addition, SSI has
14 been more fully developed as a form of pedagogy. Zeidler et al. (2005) provide a
conceptual model of SSI where students’ cognitive and moral development is encouraged
through focus on nature of science issues, classroom discourse issues, cultural issues, and
case-based issues.
Research on Reasoning and Argumentation in SSI.
Classroom incorporation of SSI involves informal reasoning, where students
develop and evaluate their own positions about complex situations (Kuhn, 1993).
Informal reasoning generally takes place when problems are ill-structured, have no clearcut answers, or involve controversy and relevant information is not readily available.
Informal reasoning includes consideration of “causes and consequences, pros and cons,
and positions and alternatives” (Sadler, 2004).
Research has revealed that individuals generally do not exhibit quality
argumentation in response to socioscientific issues. Students often fail to justify their
claims adequately or acknowledge opposing viewpoints, however several SSI
interventions have shown gains in argumentation. Zohar and Nemet (2002) found that
intervention groups of 9th grade students involved in an SSI-based genetics unit had
significant pre to post gains on a genetics-based argumentation test, while students in the
traditionally-taught comparison group did not show significant gains. Dori, Tal, and
Tsaushu (2003) also found that students improved in argumentation after an SSI
intervention, but lower achieving students had greater gains. After an SSI unit including
debate, a field trip, research, and presentation of research, Pedretti (1999) found that a
class of fifth and sixth grade students involved in a unit on mining that took place in the
classroom and a science center were more likely to consider multiple perspectives and
15 consider the ethical dimensions of problems. In a study with high school students
engaged in an SSI unit on malaria, Tal and Hochberg (2003) found that students
improved from pre to post tests on a test of argumentation. They assessed several
dimensions of argumentation basing their rubric on that of Hogan, Nastasi, & Pressley
(2000), including generativity of assertions, elaboration of ideas, number of justifications,
explanations, logical coherence, and synthesis of counter ideas. Students improved on all
subscales except synthesis. Analysis of student portfolios also showed that students
improved in their reasoning over the course of the unit and deepened their reflections. Tal
and Hochberg note that this environment enhances reasoning by creating the need to
continually present new evidence and re-evaluate thinking.
Several researchers examined student argumentation in small or whole-class
groups after SSI interventions. Albe (2008) found that SSI contexts were effective
contexts for “collaborative argumentation” where students challenged their peers to
justify positions, explain their point of view, and consider other perspectives. Zohar and
Nemet (2002) also reported gains in the quality of argumentation in group discussions.
Tal and Kedmi (2006) found that an SSI intervention for non-science majors at the high
school level improved group argumentation, including number of justifications,
incorporation of scientific knowledge, incorporation of different aspects (for example,
environmental or economic), and synthesis of counter arguments. They found that
students improved significantly in all areas except synthesis.
Sadler (2004) argues that productive interventions should facilitate students
making personal connections with the issues and stress the importance of justifying
claims and exploring conflicting points of view. He suggests that students need plenty of
16 practice with these processes, and opportunities to reflect on examples of effective
arguments. Teachers also must provide effective support in argumentation with SSI.
Finding little effect on argumentation in SSI-based classes team-taught by science and
humanities teachers, Harris and Ratcliffe (2005) concluded that a great deal of
scaffolding and support were needed in SSI classrooms. Tal & Kedmi (2006) also noted
that student gains in argumentation could have been more pronounced with greater
teacher support. They stressed the importance of teacher modeling and instruction on
argumentation, which was underrepresented in the classroom they studied. Teachers and
researchers discussed the value of team teaching in modeling argumentation, creating a
community of practice, and supporting teachers learning to teach in SSI environments.
Research on the Role of Conceptual Knowledge in SSI
Although the general literature on informal reasoning suggests that conceptual
understanding is unrelated to argumentation and informal reasoning (Sadler, 2004,
Perkins, Farady, & Bushey, 1991), studies on informal reasoning with SSI conclude that
conceptual knowledge is important to informal reasoning. Fleming (1986) and Tytler,
Duggan, and Gott (2001) found that informal reasoning was limited when participants
lacked relevant conceptual knowledge. Hogan (2002) and Zeidler and Shafer (1984)
found that conceptual knowledge enhanced informal reasoning in SSI.
Few studies of socioscientific issues took place in college settings, however
Zeidler and Schafer (1984) conducted their study with environmental science
undergraduate majors and non-science majors. Participants were assessed on content
knowledge, affect, and moral reasoning on issues related to the environment. Although
the instrument in this study targeted moral reasoning, rather than informal reasoning,
17 moral reasoning is widely accepted as an essential component of informal reasoning
(Sadler, 2004). The environmental science majors scored higher on the content
knowledge test as expected. While they were not significantly different from the nonmajors in their positive attitudes toward the environment and the general moral reasoning
measure, they scored higher in the measure of moral reasoning contextualized in
environmental issues. This study also supports the positive relationship between content
knowledge and informal reasoning in SSI.
Aside from relation of conceptual knowledge to reasoning, SSI contexts have
shown to be effective, or not detrimental to gaining content knowledge. Dori, Tal, and
Tsaushu, (2003) found that learning in SSI case studies resulted in significant gains in
content knowledge, especially for lower-ability students; while Yager, Lim, and Yager
(2006) found that SSI and traditional groups did not differ significantly in their content
learning. Zohar and Nemet (2003) found that intervention groups of 9th grade students
involved in an SSI-based genetics unit performed significantly better on a genetics
knowledge test. Also, Zeidler, Sadler, Simmons, and Howes, (2005) found that SSI
students performed better on assessments of anatomy and physiology concept knowledge
than the traditionally taught comparison group.
Barker and Millar (1996) found that in their study of 400 English secondary
students at 36 schools, students in an SSI-based curriculum, the Salters Advanced
Chemistry (SAC) course, had no significant differences from students in traditional
chemistry courses on tests of chemistry concepts. Although Barber (2001) found that
students in the SAC curriculum performed worse than those in traditional courses on a
18 standardized chemistry test, these results support Barber’s assertion that the standardized
test may have been geared toward a traditional curriculum.
Reflective Judgment in SSI
King & Kitchener’s (1994) Reflective Judgment model provides a useful
framework for considering student development in SSI. Since SSI creates contexts where
students are faced with the kinds of problematic situations that require reflective thinking,
practice and support in socioscientific reasoning should promote development in
reflective judgment. Zeidler, Sadler, Applebaum, and Callahan (2009) found that students
in two secondary level anatomy and physiology classes where an SSI curriculum was
followed showed significant development in reflective judgment between the beginning
and end of the year, while students in a non-SSI comparison group did not show change
according to qualitative and quantitative results from the Prototypic Reflective Judgment
Interview (King & Kitchener, 1994). These results indicate that a sustained SSI approach
can positively affect students’ development of reflective judgment.
Research on the Nature of Science and Scientific Inquiry in SSI
Although more research is needed in this area, SSI appear to provide effective
contexts for development of understanding of the nature of science. Khishfe and
Lederman (2006) compared two ninth grade classes, one in which NOS teaching was
imbedded in an SSI context on global warming and one in which NOS teaching was
decontextualized. NOS was explicitly addressed in both classes. Pre and post
questionnaires and interviews revealed that both groups improved NOS conceptions, but
the study did not provide evidence that an SSI environment provided advantages for
students’ development of informed NOS understandings.
19 Walker and Zeidler (2007) also investigated students’ NOS understandings in an
SSI context. They studied two mixed level high school classes working on a unit on
genetically modified foods in the WISE (Web-based Inquiry Science Environment: Bell
& Linn, 2000) computer-based learning environment which scaffolds students’ science
reasoning. NOS ideas and assessment were embedded throughout the activities. Walker
and Zeidler analyzed these assessments, data from the Nature of Scientific Knowledge
Scale, and student interviews using the Views on the Nature of Science Questionnaire
(Lederman, Abd-El- Khalick, Bell, & Schwartz, 2001). They found that students did
develop in their NOS understandings, especially in the tentative and creative/subjective
NOS. However, students did not effectively integrate NOS concepts into arguments in a
debate at the end of the unit.
While NOS describes science as an entire domain, scientific inquiry has been
differentiated as “what scientists do” (Schwartz, Lederman, & Lederman, 2008). Key
aspects of the nature of scientific inquiry (NOSI) include investigations being guided by
questions, use of different methods in scientific investigations dependent on the question,
different reasons for scientific investigations, evidence-based justification of knowledge,
recognition of anomalous data, differences between data and evidence, and standards of
practice and peer review in scientific communities. Although NOS understanding has
been studied in relation to SSI, I am unaware of published studies that explicitly address
how understanding of scientific inquiry may be facilitated in SSI environments.
Sadler (2009) states, “The one clear conclusion that can be drawn from this
section [on SSI and NOS] is that there has been more rhetoric regarding the potential for
SSI-related interventions to promote student understandings of nature of science than
20 empirical evidence.” More studies are needed to establish how teaching about inquiry and
NOS can be imbedded within SSI environments and how students are able to articulate
and apply these understandings.
In summary, reasoning with SSI should move students toward taking informed
positions on controversial issues that span scientific and social domains. Research
suggests that supporting students’ understanding of relevant science concepts and
practice with socioscientific reasoning can help students learn to develop effective
arguments in similar contexts. SSI does not appear to hinder conceptual learning, but
does appear to encourage development of reflective judgment. SSI may also be effective
contexts to help students understand the nature of science and nature or scientific inquiry.
In Human Biology, reasoning with socioscientific issues is structured throughout the
program. These activities should help students learn to advocate for particular positions
and make evidence-based arguments.
Interdisciplinary Learning
Conceptions and Origins of Interdisciplinarity
As with SSI in general, interdisciplinarity was a key aspect of the Human Biology
program, helping students develop a reflective approach to framing problems in Human
Biology. Surprisingly, to my knowledge, research and theory on interdisciplinarity have
not been connected in depth to SSI. This may be related to the fact that there is great deal
of confusion about interdisciplinarity. First, there is no agreed-upon definition. Some
consider interdisciplinary work a strictly educational domain, while others see
interdisciplinarity at work in research, government, and professions. Some view
interdisciplinary work as seeking to unify knowledge, while others see it as innovative,
21 seeking to develop new knowledge. Also the concept may be seen as merging of ideas
among the physical and life sciences, or as using disciplinary concepts to bridge the hard
sciences and the social sciences. Interdisciplinarity may also be seen as using knowledge
from an academic discipline to approach problems in professions (Thompson Klein,
1990).
Second, people are generally unfamiliar with interdisciplinary scholarly work.
Interdisciplinary professional groups are fairly new and some proponents are reluctant to
pursue interdisciplinary movements due to the narrow-mindedness that has come with
professionalization in other fields. Thompson Klein also cites a “general disinclination to
place individual activities within a larger conceptual framework or wider body of
knowledge” (1990, p. 13).
The third reason Thompson Klein cites for the confusion about interdisciplinarity
is that it has no unified discourse. Interdisciplinary spans many different literatures. The
written and spoken “texts” that are generated are not read by a common audience (1990,
p. 13).
Interdisciplinarity often originates as a result of specialization in particular
disciplines. Relationships among disciplines may emerge as in-depth study or particular
problems approach the boundaries of these disciplines. Interdisciplinary fields are often
problem-centered, drawing from different disciplines to inform different aspects of a
problem. For example, environmental psychology addresses problems that have both
psychological and environmental components. Interdisciplinarity is also called upon in
problems that are complex or have insufficient resources providing insight into those
situations (Thompson Klein, 1990).
22 People use several metaphors to understand interdisciplinarity, such as
geopolitics, the machine, and the organism. The geopolitical metaphor is commonly
applied because, in the words of Robert L. Scott, there is a “distinctly political face to the
circumstances in which interdisciplinary efforts must thrive or not.” Klein says, “If the
disciplines have become ‘warring fortresses between which envoys are sent, and
occasional temporary alliances are formed,’ then calls for ‘truth and synthesis’ are
inevitably charged with political overtones” (1990, p. 78). Disciplines maintain an
“orthodox” position of authority with perspectives viewed as doctrine with which no one
should experiment. The machine or computer metaphor has been used calling for
“interfacing” of methods and concepts to address particular problems. The metaphor of
the organism employs the idea of symbiosis of the disciplines and a fertility that gives
rise to new disciplines. Conversely, the organism metaphor is used to characterize
specialization as a pathology threatening the viability of a discipline, where
interdisciplinarity is a symptom of the disease (Klein 1990, p. 81). These metaphors
demonstrate both the political and controversial nature of interdisciplinarity.
Roles of the Disciplines
Thompson Klein (1990) defines a discipline as the “tools, methods, procedures,
exempla, concepts, and theories that account coherently for a set of objects or subjects”
Disciplines change over time in response to external and internal demands. Members of a
disciplinary community develop a “world view” specific to that discipline and establish
and hold work to criteria for excellence (p. 104-105). These are generally considered
positive aspects of disciplines, but may be seen as excluding productive ideas or ignoring
some aspects of problems (Thompson Klein, 1990).
23 Two types of interdisciplinary positions have developed. The nondisciplinary
perspective tends to treat the disciplines with disdain, viewing them as dangerously
authoritarian. For example, critical interdisciplinarity seeks to revise disciplinary theories.
The disciplinary perspective considers grounding in disciplinary work critical to
interdisciplinary work. Proponents of this perspective see a need for a “disciplinary
home,” Disciplinary theories and methods from cognate disciplines are seen as “tools” to
solve problems. The disciplines are “the base for integration, and the substance for
metacritical reflection” (Thompson Klein, 1993, p. 106).
Interdisciplinary fields are thought of as “borrowing” from established disciplines.
Reasons for borrowing include:
1.
2.
3.
4.
5.
6.
To help structure a relatively unstructured domain;
To simplify a domain;
To complete a domain;
To explain a domain;
To enable a domain to get a complete picture of its own framework;
To allow for experimentation where the domain does not permit it
(Kinneavy, 1980, p. 144; Thompson Klein, 1990, p. 85).
Thompson Klein argues that the practice of “borrowing” from disciplines is often
problematic. She says, “Resorting to ‘an alien expertise’ to solve an immediate problem
is often evidence of a ‘quick-fix mentality’ rather than a long-term, integrated solution”
(1990, p. 88). Common problems of borrowing from other disciplines include 1)
misunderstanding of borrowed concepts, 2) using ideas and methods out of context, 3)
use of borrowed concepts “out of favor” in the context in which they originate, 4)
“illusions of certainty” about concepts used cautiously in the original discipline, 5)
relying too heavily on one perspective, and 6) dismissing contradictory evidence or
explanations. (Thompson Klein). Thompson Klein argues that at least a basic
24 understanding of the disciplines from which theories, concepts, or methods are borrowed
is essential in interdisciplinary work. She calls this the “burden of comprehension” (a
term she borrowed from Janice M. Lauer).
Interdisciplinary Education
The goals and pitfalls of interdisciplinary education are similar to those of
interdisciplinarity in general, as discussed above. Goals of interdisciplinary education
include innovation, knowledge integration, student choice in inquiry, deductive
reasoning, synthesis of knowledge, and reasoning by analogy (Kavalovski, 1979; Newell
& Green, 1982/1998; Boix Mansilla & Duraising, 2007). Boix Mansilla and Duraising
(2007) define interdisciplinary understanding as “the capacity to integrate knowledge and
modes of thinking in two or more disciplines or established areas of expertise to produce
a cognitive advancement—such as explaining a phenomenon, solving a problem, or
creating a product—in ways that would have been impossible or unlikely through single
disciplinary means.”
Approaches to interdisciplinary higher education vary greatly. Postmodern
critiques have argued that disciplinary boundaries promote and protect unfair power
structures, and interdisciplinary fields, such as gender and culture studies emerged from
this perspective. Other interdisciplinary fields have developed maintaining the centrality
of a particular discipline, but borrowing from other disciplines to approach problems too
broad for traditional disciplinary approaches (Grossman, Wineburg, & Beers 2000). Boix
Mansilla, Miller, and Gardner (2000) argue that secondary education should primarily
seek to ground students in disciplines, but help students to bring disciplinary lenses
together to understand and solve specific problems. They hold that disciplines are
25 important for raising important questions, providing a time-tested conceptual framework,
and defining standards of excellence. This perspective is representative of the Human
Biology community and compatible with the goals of SSI.
Assessment of Interdisciplinary Learning
In response to the claim that university faculty are not equipped to evaluate
interdisciplinary programs or to help students understand complex, interdisciplinary
issues (Schilling, 2001), Boix Mansilla and Duraising (2007) developed an assessment
framework, identifying criteria for quality interdisciplinary work and goals for
interdisciplinary education. They interviewed faculty members at well-known
interdisciplinary programs and characterized these individuals’ analyses of student work,
such as exams, integrative papers, and capstone presentations. Data included 69
interviews of faculty and students, focusing on teaching and learning, especially
assessment, 10 classroom observations, 40 pieces of student work, and official documents
from each program.
The framework includes three areas of focus: disciplinary grounding,
“advancement through integration,” and critical awareness. Quality interdisciplinary
student work is grounded in “disciplinary theories, findings, examples, methods,
validation criteria, genres, and forms of communication.” These aspects of disciplines
employed should be appropriate to the problem and accurately applied. Important
disciplinary perspectives should be represented. Quality student work also integrates
different disciplinary ideas to advance understanding. Integrative devices include
conceptual frameworks, graphs, explanations, models, solutions to problems, or
metaphors. Finally, quality student work shows evidence of reflection and a clear sense
26 of purpose, “that is, framing problems in ways that invite interdisciplinary approaches
and exhibiting awareness of distinct disciplinary contributions, how the overall
integration ‘works,’ and the limitations of the integration.” Professors expected that
students not amass information, but use information in new situations. They should
balance perspectives in response to the purpose of the work. Students should be reflective
about the advantages and limitations of interdisciplinary work.
In summary, interdisciplinarity is a misunderstood and contentious concept
among scholars. In the Human Biology program, grounding in different disciplines offers
new tools to approach problems. The inquiry process, an important disciplinary aspect of
science, is central to learning in Human Biology. An interdisciplinary perspective should
offer students an opportunity to reflect on the purposes, advantages, and limitations of
scientific inquiry. The Human Biology program also embodies the problem-centered
nature of interdisciplinary education. Finally the program exhibits the criteria for
excellence in interdisciplinary work as discussed by Mansilla and Duraising (2007).
Coursework is grounded in the disciplines involved, students are expected to advance
their understanding through “advancement through integration” of disciplinary ideas, and
they are expected to reflect deeply on their interdisciplinary work.
Collaborative Learning
Collaborative work is an essential component of the learning environment in
Human Biology and is an essential part of teaching through SSI. A need to teach science
in the collaborative context of doing science has been emphasized in recent years.
Scientists and engineers need to work in collaborative contexts, students should have
opportunities to work together in the science classroom (Springer, Stanne, & Donovan,
27 1999). Collaborative work is a central aspect of the culture of the science disciplines,
however, as Brown, Collins, & Deguid (1989) claim, classroom contexts often “deny
students the chance to engage the relevant domain culture, because that culture is not in
evidence.”
A great deal of research has investigated the value of collaborative learning,
yielding conflicting results. A meta-analysis of group learning in college level Science,
Math, Engineering, and Technology (SMET) courses by Springer, Stanne, and Donovan
(1999) found that students involved in small group learning attained greater achievement
than students who received instruction without collaborative or cooperative grouping.
Students who worked in small groups also showed higher levels of persistence through
SMET courses and more favorable attitudes toward their classes. In his meta-analysis of
cooperative learning, Bossert (1988) found that cooperative learning can improve
students’ memory skills, retention of knowledge, and problem solving. However, a
review of literature by Davidson (1985) found that only one third of the studies examined
showed better learning outcomes with collaborative as opposed to independent learning.
Cohen (1994) suggests that the aspects of collaborative learning that lead to success only
occur in certain situations.
Some researchers have conducted studies to isolate specific aspects of the
structuring of collaborative learning environments that influence its effectiveness.
Although these studies shed light on particular aspects of collaborative learning and
problem solving, they were performed outside of the normal classroom context and used
tasks that were peripheral to the curricula. They can inform design of classroom
collaborative experiences, but a descriptive picture of the context in which collaborative
28 learning takes place is needed. The Commission on Behavioral and Social Sciences and
Education (CBASSE, 1999) recommends researchers of all educational fields come
together to investigate collaborative learning and specific problems that must be
overcome to make it effective (CBASSE, 1999, p. 280). Cohen (1994) argues that
researchers need to conduct observational studies that examine how student interaction
relates to outcome variables and allow them to make inferences about the aspects of
collaborative learning that lead to success. For these reasons, I have chosen to include
descriptive studies of collaborative learning environments which provide evidence for its
effectiveness and detail how it may be successfully implemented.
Important Processes in Collaborative Learning
Some classroom studies have highlighted the important processes in collaborative
learning that lead to effective learning outcomes. From her review of literature, Cohen
(1994) argues that elaborated discussion is central to conceptual learning. Cohen says,
“For conceptual learning, effective interaction should be more of a mutual exchange
process in which ideas, hypotheses, strategies, and speculations are shared.” Cohen
argues that the strongest predictor of achievement is giving elaborated explanations.
In their study, Okada and Simon (1997) addressed the process of collaborative
discovery learning and the role of discussion in collaboration. They questioned whether
pairs of students would perform better than individuals on a computer simulated genetics
discovery task in science, how pairs’ and individuals’ discovery processes would differ,
and what variables would impact performance in discovery tasks. Okada and Simon
found that pairs were more successful than individuals due to their participation in more
explanatory experiences, such as considering multiple hypotheses, discussing alternative
29 ideas, or considering justification. The implication of the research is that explanatory
activities help students organize information for theory-building.
Giglers and de Jong (2005) investigated how prior knowledge affects learning in a
collaborative discovery learning environment. The authors expanded Klahr and Dunbar’s
(1988) Scientific Discovery as Dual Search (SDDS) model to their own extended SDDS
model, which explains the discovery learning process between two individuals, and used
the model to interpret their results. Giglers and de Jong found that students with higher
levels of definitional knowledge were more likely to discuss interpretation of results in
problem-solving sessions, and that discussion of hypothesis generation and
experimentation was increased when dyads had different levels of prior knowledge,
although extremely different levels may have hindered success. They found a negative
correlation between number of technical remarks and the definitional knowledge test, and
a positive correlation between the definitional knowledge test and remarks related to data
interpretation. They found positive correlations between the difference in generic
knowledge test scores and hypothesis generation remarks as well as experimental design
and execution remarks. Explaining results in terms of Vygotsky’s (1978) theory of the
zone of proximal development, they conclude that heterogeneous teams were more
successful and that in a collaborative learning setting, there should be a more capable
other. They also asserted that it is important for students in a group to be aware of their
own and each others’ beliefs. This has implications for the design of the learning
environment to help make these beliefs explicit.
Hogan (1999) addresses a need for instructional methods tailored to help students
in collaborative reasoning and making sense of data in applied problems. She describes
30 the problem established in the literature that students tend to reason poorly, concentrate
on surface features, and fail to communicate equally. The purpose was to create a
collaborative inquiry intervention in which regulation of student discourse was addressed
explicitly in the curriculum. Hogan assessed competencies for knowledge co-construction
after the “Thinking Aloud Together” intervention, which explicitly stressed
metacognitive, regulatory and strategic skills. She assumed that for complex, open-ended
problems, rules or heuristics were not useful, but students needed to be aware of and able
to regulate their knowledge building processes. Four classes of eighth graders received
the intervention of a 12-week unit focusing on metacognitive knowledge, metacognitive
regulation, thinking practices, and reflection, and four control classes did not. Lessons in
the intervention group involved metacognitive knowledge, metacogntive regulation, and
thinking practices, and included a reflection phase.
Hogan found that intervention students gained in metacognitive knowledge and
ability to articulate collaborative reasoning processes. Intervention students did not,
however, show enhanced collaborative reasoning skills. Also, students with learner-asexplorer perspective had greater learning gains. Hogan suggests that the results may be
related to a lack of integration of reflection into the activities. She concludes that we need
to better understand metacognitive processes at the group level.
In response to a need for theories on how convergence of meaning is achieved,
Roschelle (1992) created and supported a process model for collaborative conceptual
change. Roschelle found that conceptual change among two female high school students
did take place in science problem solving sessions and concluded that the data provide
support for his proposed process model of convergent conceptual change. The model
31 includes the construction of the situation at an intermediate level of abstraction, the use of
metaphors in reference to the situation, cycles of “displaying, confirming, and repairing
situated actions,” and progressively requiring higher standards of evidence.
Team-based Learning
Team-based learning is a specific form of collaborative learning used in the
Human Biology program. Where other literature on collaborative learning describes
contexts in which duration of collaboration varies, team-based learning uses long term
student grouping. Although team-based learning is similar to problem based learning, the
small amount of literature on team-based learning reveals two primary differences in
structure and purpose of the pedagogy. First in team-based learning, students are asked to
apply information they have studied previously, while in problem based learning students
acquire information in the process of problem solving. Secondly, team-based learning
relies predominantly on the team structure to keep groups functioning effectively while
problem-based learning employs a tutor to facilitate group sessions (Fink, 2002).
An important assumption in team-based learning is that established teams will
perform at a higher level than their highest-achieving team member. Michaelson, Watson,
and Black (1989) investigated the differences between individual and group decision
making “in a situation that was as representative as possible of everyday work situations”
in the classroom. Previous studies had concluded that the achievement of the most
capable member of the group represented the upper limit of the group. Michaelson et al.
(1989) explain that previous studies may have failed to find higher achievement of the
group than most-capable member because groups studied had little experience working
together and tasks failed to resemble authentic tasks that teams might encounter. In their
32 study of 222 project learning teams from 25 organizational courses over 5 years, the
majority of class time was spent in group problem-solving. Students worked in the same
groups throughout the course, logging a minimum of 32 hours in group problem-solving
and data was collected from a series of six exams taken individually and as teams, a
normal part of the curriculum to which students were well accustomed. Michaelson et al.
found that in this context, teams outperformed the most successful individual 97% of the
time. While the mean score for individuals was 74.2% and the mean score for the highest
individual in the team was 82.6%, the average group score was 89.9%.
In summary, research supports the use of collaborative learning environments to
promote science conceptual knowledge and scientific reasoning. Explanatory
experiences, including consideration of multiple hypotheses, and justification of ideas are
productive processes for theory-building should be encouraged (Okada and Simon 1997).
Roschelle (1992) sheds light on important processes that take place in collaborative
science learning, including construction of the situation at an intermediate level of
abstraction, use of metaphors in reference to the situation, cycles of “displaying,
confirming, and repairing situated actions,” and progressively requiring higher standards
of evidence. Factors internal to students also affect the outcomes of collaborative
learning. Students’ prior knowledge affects their levels of interpretation of results,
hypothesis generation, and experimentation, suggesting groups should be structured for
diversity of prior knowledge (Giglers and de Jong, 2005). Finally, the perspective of the
student affects learning outcomes in collaborative environments, where a learner-asexplorer perspective has been shown to relate to greater learning gains in a collaborative
learning environment (Hogan, 1999). The collaborative aspect of the Human Biology
33 program, carried out through group discussion and teamwork should have provided
opportunities for productive cognitive processes in conceptual learning as well as
teamwork skills.
Contextualized Learning
In the Human Biology program, learning was designed to be contextualized in
real world problems that are often interdisciplinary in nature and collaboratively
approached. Work stemming from cognitive science stresses the importance of context to
learning (Brown, Collins, & Deguid, 1989). As we understand the concept of a tool
through its use, not a decontextualized examination of it, students need to experience new
concepts in the context of their discipline and application. Brown et al. (1989) argue, “by
ignoring the situated nature of cognition, education defeats its own goal of providing
usable, robust knowledge.” The context of scientific work, from lab research to
environmental science to healthcare, is collaborative. According to Brown et al. learning
is a process of enculturation. As in trade apprenticeships, learners participate in a
community with common goals. Brown et al. propose cognitive apprenticeship for
authentic contextual learning in the classroom. Students and teachers work together on
tasks authentic to the discipline of study to understand key concepts. The role of the
teacher changes from the dispenser of knowledge to a coach who helps students move
through a process of gaining experience and competence with concepts and skills. The
teacher models concepts and skills for students, allows them to practice with appropriate
scaffolding, then fades scaffolding as students demonstrate mastery.
Research on cognitive structures supports the importance of context and domainspecific knowledge (Bransford, Sherwood, Vye, & Reiser, 1986). Adams et al. (1985)
34 showed that learning activities that gave students experience with problems and showed
them how information was useful in solving those problems helped them access the
knowledge they need to solve a particular problem. Domain-specific learning promotes a
knowledge structure that allows knowledge to be accessed for relevant problems, not
remain inert.
Anchored Instruction
The approach of anchored instruction, where learning is embedded in a rich,
realistic context, is an example of situated cognition theory put into action (Cognition and
Technology Group at Vanderbilt, CTGV, 1990). This approach is intended to avoid
students’ acquisition of “inert” knowledge, knowledge acquired in a classroom context
that is generally unusable in real-life settings and may be accessed only in response to
specific cues, such as exam questions (Brown & Palinscar, 1989). Instead learning is
“anchored” in realistic “macrocontexts” similar to those in which the knowledge will be
useful. The video contexts are complex enough to encompass problem-solving from
multiple perspectives. Students are responsible to choose relevant data from the
macrocontext and generate problems that need solving from the story. In a study with the
Jasper Woodbury Adventures, a video series designed to teach math concepts through
anchored instruction, fourth and fifth grade students were found to improve in problem
generation. Also lower achievers had a higher level of participation (CTGV, 1990). This
suggests that anchored instruction can create a zone of proximal development (Vygotsky,
1978) where students are supported by peers as they participate in activities and gain
competence. This ideas of a “macrocontext” is encompassed by problem-based or casebased learning, approaches used in SSI and embraced in the Human Biology program.
35 Problem-based Learning in Medicine
The problem-based learning (PBL) model was initially developed in medical
education by Barrows and colleagues (Savery & Duffy, 1995). Research in medical
education had found that medical students retained little of the information presented in
lectures by the time they reached their clinical training, and that they did not use the
information in practice. The lecture method was criticized for allowing students to be
passive and failing to teach skills of critical thinking and problem solving. Also, medical
content is taught as isolated “facts” from the perspective of scientists rather than
clinicians (Williams, 1992). Williams argues that if biological mechanisms are only
understood independently, medical students will have trouble dealing with the variation
resulting from interaction of different mechanisms in patients. Also, real patients present
with problems with roots in psychology rather than biology, and decisions and abilities to
seek treatment depend on many social and economic factors. Medical education should
prepare students to deal with these issues of uncertainty.
Savery and Duffy (1995) describe the constructivist principles on which PBL is
based: anchoring activities into a broader problem, helping students to take ownership for
the problem, engaging students in an authentic task, matching the complexity of the task
to that of the environment in which knowledge will be used, allowing students to take
ownership of their problem-solving process, supporting and challenging students’
thinking, encouraging social negotiation and testing of ideas, and supporting reflection on
content and process. In PBL, social negotiation of meaning and metacognitive skills are
essential, since PBL teams must monitor their understanding and progress (Savery &
Duffy, 1995).
36 Hmelo-Silver (2007) explains that PBL presents students with complex problems,
but provides scaffolding that makes tasks “accessible, manageable, and within students’
zone of proximal development.” Collaborative groups allow complexity to be reduced
through pooling ideas and experiences and sharing work load. Tutors help groups to
manage interactions and engage in productive reflections, and white boards help groups
to organize and keep track of information. Also the sequencing of PBL is intended to
provide scaffolding by increasing the level of detail as students gain competency. PBL
emphasizes students understanding the reasoning behind a process as well as the process
itself (Hmelo-Silver, 2007).
In studies, PBL has been found to increase motivation, self-directed learning, and
the opportunity to integrate science into real problems (Hmelo & Evensen, 2000).
Reviews of literature by Albanese and Mitchell (1993) and Vernon and Blake (1993)
reported that PBL students scored higher on clinical assessments than traditionally
trained medical students. Dochy, Segers, Van den Bossche, and Gijbels, (2003) found
that PBL students scored higher than traditional students in tests of knowledge
application. According to another analysis of literature by Norman & Schmidt (1992),
although PBL may initially result in decreased learning as compared to traditional
teaching methods, it increases retention of knowledge. The analysis also suggests that
PBL could facilitate transfer to other problems and help students integrate science
concepts into a clinical context. Also, PBL increases students’ intrinsic interest in content
and improves self-directed learning skills (Norman & Schmidt, 1992).
Some authors have found PBL ineffective for some aspects of student learning. In
their metaanalysis, Albanese and Mitchell (1993) found that PBL resulted in lower scores
37 on basic science exams, and students spent more time studying. Colliver (2000) found no
statistical differences between PBL and traditionally taught students on standardized or
course exams for first and second year medical students. Vernon & Blake (1993) found a
decrease in basic science scores of PBL students and Dochy et al. (2003) found no
difference in tests of declarative knowledge. In their review of literature, Norman &
Schmidt (1992) reported no difference in problem solving skills between PBL and
traditionally taught students.
Hmelo-Silver (2007) argues that most literature comparing PBL and traditional
curricula is “reactive,” where data are presented in such a way to support a particular
position toward it. Also PBL students generally opt to participate in that track, so students
are not randomly assigned (Hmelo-Silver, 2007). Although PBL students may perform
lower on basic science exams, PBL has positive effects on processes important for
practice, such as tests of clinical knowledge, transfer of knowledge to new problems, and
hypothesis-driven reasoning.
Problem-based and Project-based Learning
Sherwood, Petrosino, Lin, and the Cognition and Technology Group at Vanderbilt
(1998) discuss problem-based macrocontexts, an example of an anchored instruction
learning environment. Design principles for this learning environment include a narrative
format, “generative design of stories,” data embedded within the context, complex
problems, use of video, connections across curricula, and paired episodes to promote
transfer of concepts. Problem-based macrocontexts allow students to undergo an iterative
process of exploring, assessing and revising their understanding. The use of video helps
students to recognize relevant information. Sherwood et al. (1998) base their design
38 principles on concepts of cognitive science: collaborative inquiry, real world problems,
incorporation of technology, and modeling a research community in the classroom.
In a preliminary study of the problem-based macrocontext, Scientists in Action,
two groups of students studied the same content by reading a book chapter. The
intervention group then watched the Stones River Mystery video, which was relevant to
that content, while the control group watched a video developed to situate different
content. Sherwood et al. (1998) found that the intervention group performed at a higher
level compared to the control group on measures of motivation, problem-solving and
noticing relevant information for problem-solving. However to effectively use this model,
teachers must develop a student-centered style of teaching and face such challenges as
allowing students to come to their own solutions, even when on wrong pathways, to
know when to intervene versus allowing students to struggle, and integrating materials
into the curriculum.
Barron et al. (1998) also encourage the combination of problem-based and
project-based learning. They describe their version of problem-based learning as “the use
of authentic but simulated problems that students and teachers can explore
collaboratively.” They describe project-based learning as taking place in everyday
environments and having tangible outcomes, whereas simulated environments are
considered problem-based. Barron et al. identify four principles of design for problembased and project-based learning: developing “learning-appropriate goals that lead to
deep understanding,” preceding project-based assignments with problem-based ones and
incorporating scaffolds like embedded teaching and contrasting cases, providing
opportunities for revision and reflection, and social organization to promote students’
39 sense of agency. They suggest that using problem-based and project-based learning
together allows students to develop shared knowledge and skills through work on a
problem, then apply that knowledge to a project. Work on the project further develops
skills and deepens understanding of concepts.
Barron et al. (1998) describe a problem-to-project intervention called SMART.
The students are first involved in a problem anchored in a video-based story, which
requires them to develop a blue-print. Students receive formative assessment on their
blueprints and undergo a process of revision using media and peer resources. Students
use the knowledge and skills developed while working on the problem to collaboratively
design a playhouse taking certain constraints into consideration. Students undergo a
process of revision throughout the project, and at the completion, present the project to
their peers. All members of the class participate in evaluation of the project. Barron et al.
assert that the presentation is important to help students reflect on “what it means to
explain one's thinking and how to convince someone of the accuracy of a plan as well as
issues such as what makes a presentation engaging.” Evaluating five classes of fifth
graders on their blue-print designs of a chair, their achievement on a standards-based
geometry test, and collaborative playhouse designs, Barron et al. found that all levels of
math students improved substantially in their abilities to apply, understand, and present
geometric concepts. Also, they found that students took advantage of the opportunity to
revise their ideas.
Case-based Learning
Case-based learning has been used for many years in business and legal
education. Like cognitive apprenticeship and anchored instruction, this approach
40 contextualizes concepts and provides scaffolding for learning. It provides authentic
activities for learning, which Williams (1992) defines as “coherent, meaningful, and
purposeful,” and representative of the activities members of a culture actually participate
in. Like anchored instruction, the contexts for case-based learning are complex. The case
method is often used for ill-structured problems, which lack “a consistent underlying
theory that can act as a structure for organizing knowledge” (Williams). The case method
in law does not emphasize collaborative learning, but is social in nature in that it involves
group discussion and a public forum for Socratic questioning. Kolodner, Hmelo, and
Narayanan (1996) stress the cognitive factors of case-based reasoning, like “access to old
experiences (cases), and use of old experiences in reasoning” in design of effective
learning environments. They explain that case-based reasoning is based on making
inferences from specific and “cohesive knowledge structures” which link specific aspects
of situations. Learning in CBR takes place by interpreting and committing to memory
new experiences, re-interpreting previous experiences so they may be more easily
indexed, and making generalizations from multiple experiences.
Williams (1992) discusses case-based learning and problem-based learning in
terms of several criteria. The learning experience should begin with a problem, the
teacher should model expert problem solving, and students must be given opportunities to
solve problems on their own with scaffolding and immediate feedback from the teacher.
Instruction should stress metacognitive strategies and frequent formative assessment by
both teachers and students. Problems should be authentic, complex, and target multiple
skills. Formats, such as story or video should help to make the problem manageable and
41 problems should be sequenced to meet students’ needs as they progress through the
course.
Modification and Integration of PBL and Case-based Reasoning
Williams (1992) suggests that theories from cognitive apprenticeship and
anchored instruction may improve the effectiveness of problem-based learning and the
case method. She argues that expert models should be available to students so they may
understand the thinking processes involved in solving contextual problems. Also, cases
should target a wide range of skills. Efforts should be made to reduce complexity of cases
by using story or video formats. This could facilitate novices’ learning of domain specific
vocabulary. Cases should be sequenced according to difficulty and diversity to reduce
student frustration and facilitate their progress. Also, attention should be paid to helping
students pick out important information. Presenting the same concept in multiple contexts
like hypothetical situations may help students in this goal. These methods should engage
students in “learning to learn.” Giving students opportunities to actually apply
knowledge, as in project-based learning is also important as well. Lastly more frequent
opportunities for assessment would improve the effectiveness of these instructional
models (Williams).
Kolodner, Hmelo, and Narayanan (1996) recommend combining features of casebased reasoning and PBL. The two methods are complementary because PBL provides
students with cases they may use to reason in future problems and CBR encourages
students to reflect on the lessons that come out of each experience and predict how those
lessons may apply to future situations. CBR also stresses the importance of feedback to
identify flaws in thinking and missing knowledge. When using knowledge from an old
42 experience fails in a new experience, the learner reevaluates the old situation. In
developing problems, Kolodner et al. (1996) argue that failures are important, but should
be handled gently, so “students understand their role in learning.” Working with others
can also enhance CBR by increasing the number of available cases from which to reason.
While PBL suggests indexing cases to develop learning issues for problem solving, CBR
suggests indexing cases to predict effects of problem solutions. Looking forward to other
situations in which knowledge from the current case may be useful, as well as looking
backward to search memory for similar experiences may promote transfer (Kolodner et
al.). Kolodner et al. suggest incorporating tools, like case libraries which help students
compare cases, determine what is important to take from cases, and test their ideas. They
also suggest that when tutors are not available, scaffolding may be provided in a
computer environment. A computer environment may also facilitate reflection to enhance
transfer.
In summary, anchored instruction, problem-based learning, project-based
learning, and case-based reasoning provide models for learning science in the context of
authentic problems. Focus on domain knowledge should help students to develop
knowledge structures that help them access relevant information in problem solving. In
addition, instruction drawing from these models should encourage students to engage in
reflection to make knowledge explicit and elaborated, monitor and assess their learning
process, and develop strategies for more effective learning.
Relation to Study
The goals and pedagogy of the interdisciplinary Human Biology program were
grounded in research from many related fields in science education and learning sciences.
43 The core courses integrated different disciplinary perspectives and facilitated student
reasoning in the context of socioscientific issues, encouraging development of crossdisciplinary thinking and evidence-based decision making. A collaborative, team-based
environment was used to facilitate both learning of content and development of reasoning
processes. Learning in context of problems and case studies was emphasized to help
students develop knowledge they can apply to future situations. These research-based
features of the Human Biology program contrast the traditional lecture-based and
content-driven college biology learning environment. This dissertation investigates how
participation in this learning environment affects student outcomes and perceptions of
learning experiences.
44 CHAPTER 3: METHOD
Context of Study
The study took place in a large research-oriented university. Participants were
recruited from the Human Biology program and the traditional biology major. Since I
focus on the SSI-based context of the Human Biology program, I will refer to this group
as SSI and the biology group as BIO. These majors differed where, in addition to
required and elective courses, all SSI majors took yearly core courses and seminars and
maintained a four-year reflective portfolio. BIO majors created a cohesive curriculum of
required and elective courses, but were not involved in longitudinal projects or yearly
core courses. In the SSI major, case-based socioscientific reasoning was deliberately
structured into all core courses, with a developmental focus on moving students from
exploring different perspectives to position-taking and advocating for evidence-based
positions. For the SSI group, I will provide an in-depth description of the class context
and activities used to specifically teach SSI. I will then describe the comparison (BIO)
group in terms of curriculum and general teaching methods.
SSI Group
The published mission of the Human Biology program was “to integrate the
biological and social sciences with the humanities and the arts in the study of human
beings and the human condition” (Human Biology, 2007). Students enrolled in the
program planned to enter life science graduate programs or professional programs, such
as medicine, nursing, dentistry, physical therapy, law, or journalism, or pursue careers in
teaching, the life science industry, or public policy. The program included selected
courses from four concentration areas: human environment and ecology, human origins
45 and survival, human health and disease, and human reproduction and sexuality, as well as
a series of interdisciplinary core courses taken each year.
The foundation of the program was established in yearly core courses. These
interdisciplinary courses connected primary biological concepts with related social and
ethical issues and explicitly addressed epistemological concepts in biology including
uncertainty, tentativeness, and the centrality of evidence to knowledge in biology
(Human Biology, 2007). The interdisciplinary nature of the program responded to recent
trends, including converging fields of disciplinary knowledge, professional requirements,
and the need to solve problems that are both social and intellectual in nature (Thompson
Klein, 1990). Core courses were team taught by an expert from the sciences and another
discipline, and the specific course topic depended on the expertise of the instructors.
Key themes running through these courses included scientific literacy through
position-taking on socioscientific issues, collaboration, contextualized learning, and
reflection. Scientific literacy includes “informed decision-making, the ability to analyze,
synthesize and evaluate information, dealing sensibly with moral reasoning and ethical
issues, and understanding connections inherent in socioscientific issues” (Zeidler, 2001).
In the Human Biology core classes, scientific literacy was conceptualized to connect the
inquiry process with social context, historical context, and ethical context (Human
Biology, 2007). These efforts toward scientific literacy echo the goals of Socioscientific
Issues (SSI). Understanding of SSI in Human Biology was developed through discussion,
peer evaluation, and service learning. Contextualizing learning in case studies promotes
ethical development through consideration of how power and authority influence
scientific endeavors (Zeidler and Keefer, 2003).
46 Student collaboration was a central component of the SSI program (Human
Biology, 2007). Students worked in teams for entire semesters on case studies, course
projects, and even exams. This aspect of the program is based on evidence for the
effectiveness of collaborative learning and scholarly work on best practices in team-based
learning (Fink, 2002, Schlegel & Pace, 2004).
Contextualizing learning in scientific problems through case studies and service
learning projects was also an essential aspect of the program. Like the similar
instructional strategies of problem-based and case-based learning, problems addressed in
core courses are complex, target multiple skills, and resemble the activities in which
members of a culture actually participate. Within the case context, the instructors provide
models of expert problem solving (Williams, 1992). The team teaching approach allows
students to see integration of different perspectives to solve problems.
Reflection and documentation of content learning, collaborative processes, and
personal experiences are scaffolded through class discussions and a progressive
electronic portfolio which individuals update throughout the entire program. Technologybased reflective scaffolds have been found effective to help students articulate ideas and
develop and reflect on explanations (Land & Zembal-Saul, 2003).
In the following section, I will provide context for the teaching of SSI in the two
core courses I observed: the 200 level and 400 level courses.
200 Level Core Course
The syllabus describes the primary objective of the course as follows:
This course introduces the social and ethical dimensions of human
biological experience and the construction of scientific knowledge through
in-depth consideration of human death and disease…we will use a
collaborative, case-based approach to explore the operationalization of
47 scientific concepts, the logic of scientific inquiry, and the effective
communication of evidence, interpretation, and claims.
Learning goals included constructing models integrating different fields of science,
gathering, evaluating, and applying scientific data to understand patterns of disease and
death, evaluating different perspectives on death and disease and arguing a chosen
position using scientific evidence, and developing a portfolio in areas of inquiry of
personal interest.
The structure of the course was team-based. Teams of 5-6 students collaborated in
and out of class, and the majority of class time involved teams working together on
particular tasks, generally case studies, followed by whole class debriefing. Since the
course depended on active student involvement, participation and peer evaluation made
up 20% of the course grade. Other activities included short lectures by instructors, guest
lectures, short individual assessment activities, team presentations, and exams. In class,
teams were seated around individual tables to encourage team interaction. Each table was
equipped with at least one laptop to research topics and create documents. The
atmosphere of the classroom was energetic and informal, with the majority of interaction
within teams.
Like most of the core courses, the class was team-taught by an expert in the
biological sciencese (in this course a neuroscientist) and an expert from the social
sciences or humanities (in this course a sociologist with specialization in epidemiology).
Generally, one professor presented new information and when cases were discussed, each
professor modeled his or her disciplinary perspective and the importance of integrating
those perspectives. They were honest about the limitations of their knowledge and
participated in information searches when difficult questions arose.
48 The course was structured into three modules: death and dying, infectious disease,
and HIV and AIDS. These modules focused on understanding operational definitions of
death and disease for different contexts, physiological and microbiological understanding
of these topics, understanding of these topics at multiple scales, and use of scientific
information in arguing positions. I will describe activities from the third module in depth
to demonstrate how the course was designed to encourage effective reasoning with SSI,
teach science content in context, help students evaluate differing perspectives and
develop and argue their own positions.
The third module spanned approximately four weeks. The stated goal of the
module was, “We use in-depth analysis of HIV/AIDS to investigate how complex
pathogens, politics, and ideologies contribute to infectious disease epidemics locally and
globally.” Specific learning goals included biology content, such as differentiating
between viruses and retroviruses, analysis of public epidemiological data, and
argumentation regarding political and ideological controversies around the disease. The
largest part of the module included discussion of a controversy ignored by most scientists
and the media over whether the HIV virus actually causes AIDS, which was presented in
two papers from the journal, Science (Duesberg, 1988 and Blattner, 1998). Before class,
students read the position papers and completed a reflective writing assignment asking
them to answer why they do or do not believe HIV causes AIDS, what issues were
important from the readings, and five areas they needed to learn more about to resolve the
problem. Team members were instructed to share their responses, pool knowledge and
research some answers to questions they had identified. They were also asked to develop
a consensus list of key issues from the readings. To better understand Duesberg’s
49 argument against HIV as the causative agent in AIDS, each team was assigned one or two
of Duesberg’s ideas to investigate and explain in depth for the next class. Students used
additional sources to develop short presentations on such topics as accepted postulates of
virology, normal characteristics of retroviruses, and normal presentation of disease after
viral infection.
Students’ final assignment for “The Duesberg Phenomenon” was to present an
argument supporting or refuting Duesberg’s argument. One professor explained the
assignment, emphasizing that students should focus on making good arguments.
Students’ handout read, “Your goal in your investigation is to evaluate Duesberg’s
position and that of his critics with reference to current scientific knowledge. As you
evaluate their positions, consider what we have learned about evaluating scientific
evidence: for which side is the evidence strongest? What additional information is needed
to fully evaluate the competing positions?” Students were told they were expected to
consult relevant sources other than those provided to the class, finding information that
was current and reliable. Each team was expected to define both Duesberg’s and
Blattner’s positions clearly and use evidence to make an argument for their positions.
Students made 5-7 minute presentations, answered questions posed by their peers and
professors, and turned in a summary of their argument.
In the second part of the module, students considered government responses to the
AIDS epidemic, using the contexts of Brazil and South Africa. First the class was
introduced to Brazil’s position rejecting funds from the United States, which were set
aside for AIDS programs on the condition that the country make a declaration
condemning prostitution. The students were asked to consider, “Is it appropriate for the
50 U.S. government to place ideological constraints on funding for global health
initiatives?” Teams were split in half by “yes” and “no” positions, and were instructed to
develop “logical evidence based arguments” for assigned positions. Each side was given
about 30 minutes to research their positions, and then they made their arguments to their
team members. As a class they presented preliminary points for “yes” and “no” positions.
The teams then developed consensus positions and arguments supporting their positions
incorporating background information on the history of US funding for AIDS programs
and of AIDS in Brazil. In a handout they were told, “The most effective arguments will
take into account the points made by the opposition.”
For their final projects, teams were assigned a paper comparing and contrasting
how AIDS is experienced in Brazil and South Africa, and presenting a “multiscalar
model of AIDS.” Teams were expected to integrate aspects of the biology of AIDS with
epidemiological data, prevention strategies, treatments, and factors influencing treatment
of individual patients in each country. Teams were required to provide a visual
representation of the model with a complete description.
400 Level Core Course
This core course titled “Complex Problems of Humanity” was considered the
capstone for the Human Biology program and was geared toward student advocacy.
Unlike the other three core courses, it was not team-taught, but lead by the director of the
program. The course was primarily collaborative and project-based and students took
responsibility for the direction of the course. It involved service learning components,
working with other organizations to participate in the National Global Warming TeachIn, and work with the local Parks and Recreation Department to assess and research local
51 water quality. This course focused not only on understanding socioscientific issues and
arguing positions based on evidence, but challenged students to organize and act based on
these positions. The course description in the syllabus read as follows:
In this course students will focus on significant problems at the interface
of science and society, such as global warming, water contamination and
scarcity, fossil fuel exploitation, insufficient global healthcare, and
inefficient use of dwindling land resources. Students will advocate for
change so as to persuade policy makers and community leaders to support
change using innovative approaches that reflect the foundations of science.
Learning goals included engaging scholars in an endeavor to educate the community
about the complexity of problems and the need for different perspectives in finding
solutions, understanding of different dimensions of problems from local to global,
understanding advocacy through individual reflection and team work, and learning how
to confront challenges as “an engaged citizen with an evidence-based approach to
advocacy.”
Three full modules were completed in the course. The first module was intended
to educate the public and focused on global warming. The second module, intended to
engage students in the community, included a service learning project with local Parks
and Recreation and a state river water quality program. In this module, students
researched the definition of a water shed, reflected on films and completed case studies
on ecological and political concerns involving water, and connected this knowledge to
local water issues through collecting water samples and conducting original research
projects. The final project included group poster presentations of this research open to the
university and community. The third module included a personal reflection on advocacy
through an audio-recorded “This I Believe” statement. To illustrate how goals of SSI
were enacted in this course I will discuss the first module in-depth.
52 The four week global warming module began with general education on the
subject through independent study and discussion of various readings including Gore’s
(2006) An Inconvenient Truth. The majority of class time was spent on the collaborative
project of planning and holding an on-campus teach-in incorporating the goals of the
National Teach-In (http://www.nationalteachin.org).
Students were expected to review the goals of the National Teach-In and review
the scientific data and human and ecological implications of global warming
independently. In class, students were introduced to two graduate students from biology
and political science who organized the first teach-in at the university the previous year.
These graduate students described the outcomes of the previous teach-in as well as
specific challenges and suggestions for the next one.
The majority of class time was spent on organization of the event. The professor
led a team-building activity where students grouped themselves according to their styles
of working in teams. They expressed the strengths and weaknesses of their team work
styles and what others needed to know about them to work effectively. Some described
themselves as detail-oriented, others as big picture-oriented, some as most concerned
about getting things done, and others with understanding different points of view. This
activity prepared students to approach a difficult and complex task with understanding
and strategies for incorporating different approaches.
After having opportunities to brainstorm ideas for the teach-in with input from the
graduate students, students were asked to condense and report their goals for the teach-in.
These included clarifying myths about global warming, getting good attendance,
motivating participants, educating participants on how they could help, providing
53 information on local resources for energy conservation, becoming more fluent with ideas
and vocabulary related to global warming, and making impacts like reducing carbon
footprints and improving health. Students shared ideas for local groups and professors
who might prepare presentations or exhibits for the teach-in. They were also given
opportunities to ask questions of the class. They shared what they knew about contacting
politicians, how human health can be related to global warming, and what kinds of visual
aids might be useful for conveying the environmental impact of global warming. For the
remainder of the module, students worked in groups to reserve a room in the student
union, book speakers and representatives of community resources to meet goals
previously specified, manage funding resources and ask businesses for donations, and
decide on schedule and room layout issues.
The teach-in lasted a full day and was well attended by students, professors, and
passers-by. Several representatives of local conservation resources were available for
consultation, professors gave presentations on relevant research, and brochures and
student-developed educational resources were available. At the end of the module,
students were asked to reflect upon the experience, including conceptual learning as well
as personal and team-building experiences. They prepared a list of effective strategies
and suggestions for future teach-ins. Overall in this module, students studied the
scientific and social implications of global warming, developed informed positions about
what could and should be done about the issue, and advocated for their cause through a
collaborative effort combining local and national resources. This activity not only helped
them reason in a socioscientific context, but to put their knowledge and personal
54 positions into action. This required reaching consensus among many different individual
perspectives to create and carry out specific goals.
Biology Comparison Group
BIO majors were recruited as a reasonable comparison group to SSI majors,
considering they take many of the same courses and pursue similar career and
professional paths. Although their coursework is very similar to SSI majors and they take
many of the same courses, they were chosen as a comparison group because they did not
participate in the series of core courses, Human Biology community events, or portfolios
which were designed to develop socioscientific reasoning and promote reflection on
interdisciplinary, biology-related issues. Since there were no correlates to Human
Biology core courses and individual programs of study varied greatly, I will describe the
basic curriculum and major goals.
The Biology major offered Bachelor of Arts (B.A.) and Bachelor of Science
(B.S.) degrees. The B.A. required three more foreign language courses and six more
courses in arts, humanities, cultural studies, and social or historical sciences, four fewer
courses in chemistry, physics, and math, and two fewer upper level biology courses. The
same core courses in introductory biology, molecular biology, and evolution were
required for both degrees. Many of the courses had associated labs. Based on my limited
observation of biology courses (molecular biology), participation as a lab instructor
(histology), and student interviews, I understood that biology courses were primarily
lecture-based. In lecture sessions, professors usually used slideshow presentations and
students took notes. Students were given opportunities to ask questions, and many large
courses scheduled discussion sessions with graduate instructors, where students worked
55 on problem sets or brought questions on course material. Lab courses offered students
opportunities to learn techniques and verify concepts taught in class, and in some
instances were inquiry-based where students independently investigated their own
research questions. Although we could not verify that all biology courses did not have
SSI components, no biology course descriptions reviewed included SSI, and none of the
16 students interviewed reported having been involved in significant in-depth discussion
of SSI in biology courses.
Methodology
Worldview
I approached my research from a worldview incorporating elements of
pragmatism and constructivism (Creswell & Plano Clark, 2007). This is consistent with
Creswell’s and Plano Clark’s worldview stance 2, which states, “Researchers can use
multiple paradigms or worldviews in their mixed methods study” (2007, p. 27). From a
pragmatist perspective, I approached the study asking “what works,” specifically, what
are the significant differences in outcomes and experiences in students who choose an
alternative program as opposed to those who choose a traditional major? Creswell and
Plano Clark explain that in a pragmatist approach the researcher takes multiple stances,
some of which are biased and some which are unbiased. Combination of qualitative and
quantitative research methods is appropriate to this worldview (p. 24).
Where a pragmatist approach may combine elements of post-positivism and
constructivism, within this approach I lean toward a constructivist worldview. Within the
question of “what works,” I recognize multiple realities. Although I hope to reveal trends,
I also seek to bring out different perspectives of participants. The majority of the study
56 takes an inductive approach, beginning with students’ understandings and looking for
themes or trends. Appropriately, the majority of my study is qualitative in nature, using
semi-structured interviews and open-ended surveys where codes emerge from student
responses (Creswell & Plano Clark, 2007, p. 24)
Research Design
The design for this mixed methods study is consistent with the triangulation
design, in which qualitative and quantitative methods are combined “to obtain different
but complementary data on the same topic” (Morse, 1991, p. 122, Creswell & Plano
Clark, 2007 p. 62). Combination of qualitative and quantitative data helps to validate or
problematize findings from individual sources. Although in part of my study I transform
qualitative questionnaire data into quantitative results, (consistent with the Data
Transformation Model), the Convergence Model best describes my study. In this model,
both qualitative and quantitative data are collected and results are converged. To interpret
results, outcomes of each component are compared and contrasted to validate or further
explain a phenomenon (p. 64-65). I consider my design to be concurrent, since data was
primarily collected in one phase (p. 81). Interviews and observations were conducted in
the same phase as the questionnaires, although questionnaires of only interviewed
students were reviewed prior to interviews to allow me to check validity of
questionnaires and probe any unclear aspects of questionnaire responses.
Participants
Participants included students at the mid-point and end of their college careers.
These groups were chosen because the Human Biology senior class was very small (19
students), and both 200 level and 400 level core classes were in session. 200 level
57 participants included 30 SSI students (77% of the class) and a matching sample of 30
BIO students, and 400 level included 15 SSI (79% of the class) and 20 BIO students. SSI
students were recruited from core classes, and BIO majors were recruited from biology
classes at the 200 and 400 levels. The only criteria for participation in the study were
major and level of progression in the major, as determined by the levels of recruitment
courses. I recognize the convenience sample was not ideal, but reasonable to make data
collection feasible. Recruitment courses included two sections of 200 level molecular
biology (approximately 200 students each) and four lab sections of 400 level Human
Tissue Biology (approximately 120 students total). SSI students were recruited first, and
recruitment of BIO students continued until nearly equal sample sizes were reached.
Payment of twenty dollars served as an incentive to participate in surveys, and those who
were willing to participate in interviews were treated to coffee during the interview.
For the SSI group, 200 level students included 23 females and 7 males and 400
level included 14 females and 1 male. For BIO, 200 level students included 18 females
and 12 males, and 400 level included 10 females and 10 males. Self-reported ethnicities
for 200 level SSI stuents included 21 White, 4 African American, 1 Multi-racial, 1
Hispanic, 1 South Asian, 1 Greek, and 1 not identified. For 400 level SSI students, 11
reported themselves as White, 1 as African American, 1 as Hispanic, and 2 as Multiracial. For 200 level BIO, 28 reported themselves as White, 1 as Asian, and 1 as Middle
Eastern. For 400 level BIO students, 12 reported themselves as White, 2 as African
American, 4 as Asian, and 1 as Middle-Eastern, and 1 was unidentified.
Overall, SSI and BIO participants reported similar professional goals and grade
point averages (with BIO students approximately .2 points higher on a 4 point scale; see
58 Table 1). SSI and BIO students were nearly equal in students planning to go to medical
school and graduate school or research. Small but comparable numbers of students from
each program planned to study law, public health or social work, and nursing. A greater
number of BIO students planned to enter other graduate level health professions, like
dentistry, optometry, and physical or occupational therapy. Responses to why students
chose their majors indicate that the biology major was a close fit to the requirements for
these professional programs. SSI students were slightly more likely to plan to enter the
workforce or to obtain a business degree.
Minor choices reveal some differences in focus of study between SSI and BIO
participants. Minors are reported by adding together all minors listed by students in each
group. Some students had multiple minors and some had no minor. Multiple minors in
one category for one student were counted as one minor (one instance). Double majors
were few, but were included as minors because they illustrate additional expertise. BIO
students were more likely to have multiple minors than SSI students (43% vs. 17%
respectively in 200 level classes and 55% vs. 40% in 400 level classes). This could be
due to the interdisciplinary nature of the Human Biology program. Since focus areas
allow students to explore areas outside of biology, a minor may not be viewed as
necessary to illustrate expertise. SSI participants were more likely to minor in psychology
or business. These students may be more interested in behavioral aspects of humans.
More SSI participants minored in biology, exercise science, or nutrition, by taking
enough additional biology courses to meet the qualifications. It is important to note that
the biology minor was only an option for SSI students. BIO students were much more
likely to minor in chemistry. Informal discussions with students suggest this is because
59 the requirements for the biology major include a great deal of chemistry. BIO students
were also much more likely to minor in areas of the humanities, such as foreign language,
literature, creative writing, music, or visual arts. The reason for this is unclear, although a
more focused curriculum may offer more flexibility to pursue an additional focus area.
Groups were similar in social science minors and public health.
Table 1
Demographic information for SSI and BIO participants.
SSI 2
n=30
Career Path
Medicine/PA
Nursing
Other grad health
profession
Work/other
Graduate
School/Research
MBA
Public Health/Social
work
Undecided/unknown
Law
Minor
Psychology
Other social science
Human Sexuality
Humanities
Business/Manage-ment
Public Health
Biology/Exercise
Science/Nutrition
Chemistry
Information Technology
none
Average GPA
Lab Experience
(n/n reported)
Teaching Experience
(n/n reported)
BIO2
n=30
SSI4
n=15
BIO4
n=20
SSI Total
n=45
BIO Total
n=50
13(43%)
3(10%)
4(13%)
13(43%)
2(7%)
9(30%)
5(33%)
1(7%)
4(27%)
6 (30%)
0
8(40%)
18 (40%)
4(9%)
8(18%)
19(38%)
2(4%)
17(34%)
2(7%)
3(10%)
0
4(13%)
2(13%)
1(7%)
0
2(10%)
4(9%)
4(9%)
0
6(12%)
2(7%)
0
0
0
0
2(13%)
0
1(5%)
2(4%)
2(4%)
0
1(2%)
2(7%)
1(3%)
1(3%)
1(3%)
0
0
2(10%)
1(5%)
2(4%)
1(2%)
3(6%)
2(4%)
9(30%)
4(13%)
2(7%)
7(23%)
5(17%)
0
3(10%)
5(17%)
4(13%)
0
13(43%)
0
1(3%)
2(7%)
6(40%)
3(20%)
1(7%)
1(7%)
0
1(7%)
3(20%)
5(25%)
6(30%)
0
4(20%)
2(10%)
1(5%)
0
15(33%)
7(16%)
3(7%)
8(18%)
5(11%)
1(2%)
6(13%)
10(20%)
10(20%)
0
17(34%)
2(4%)
2(4%)
2(4%)
1(3%)
0
5(17%)
3.20
3/27
(11%)
4/27
(15%)
(30%)
1(3%)
6(20%)
3.41
7/30
(23%)
4/30
(13%)
4(27%)
0
2(13%)
3.32
3/13
(23%)
6/13
(46%)
13(65%)
1(5%)
1(5%)
3.41
6/18
(33%)
8/18
(44%)
5(11%)
0
7(16%)
3.26
6/40
(15%)
10/40
(25%)
22(44%)
2(4%)
7(14%)
3.41
13/48
(27%)
12/48
(25%)
SSI and BIO participants both reported that one fourth of the groups had
experience teaching, including undergraduate teaching assistantships, teaching programs
60 for children, and health-related training programs. BIO students were about twice as
likely to have participated in a research group (BIO: 27%, SSI 15%). Although the
Human Biology program worked to encourage undergraduate research, surveys suggested
biology majors may have participated more to be competitive for professional programs.
General Procedures of Data Collection
Recruitment
Participants were recruited from 200 level and 400 level classes and lab sessions.
Since all SSI students at the 200 and 400 levels were currently enrolled in core courses,
recruitment was conducted at the end of these class sessions. For BIO students, I
consulted with the director of Human Biology who was also a biology professor to
choose comparable classes to recruit biology majors. BIO participants were recruited
from two 200 level molecular biology lecture classes and four lab sections of a 400 level
human tissue biology class. This course was chosen because of its human focus. In each
class, I presented an overhead slide explaining the purpose of the study, the compensation
of 20 dollars for participating in the 75 minute questionnaire, and the available times to
complete the questionnaire in a computer lab on campus. At the end of class I provided
sign-up sheets for students to choose a time to complete the questionnaire. One to two
days before scheduled sessions I sent email reminders to participants.
Collection of Questionnaires
I oversaw each questionnaire session in computer labs on campus. First students
read and signed a consent form to participate in the study. They then completed a written
demographic information page (see Appendix C), which asked students to submit an
identification code, as well as demographic data, major, minor, career plans, and
61 activities. While completing these sheets, students were emailed links to the Biology
Concept Inventory and a Survey Monkey link, which included the questionnaires on SSI
(DMQ) and scientific inquiry (VOSI; see Appendix D). Students identified themselves in
the Survey Monkey questionnaire with the identification code entered on their
demographic sheets. Students were allowed as much time as they needed, but in general
spent one hour to 75 minutes.
General Interview Procedure
Demographic sheets of students who checked a box on their consent forms
indicating that they were willing to participate in an optional interview were separated by
year and major. I interviewed a subset of sixteen participants (four from each group by
year and major). SSI participants were chosen to best represent the population of the
small program by sex and ethnicity, then to provide a variety of grade point averages and
course backgrounds. BIO participants were chosen to match SSI participants as closely as
possible by these criteria. No male students from the 200 level BIO group were available
for an interview, so only female students were interviewed.
Those willing to be interviewed made arrangements to meet me in a neutral
environment like a coffee shop. They were treated to coffee as compensation. The
interviews followed a semistructured interview protocol (see Appendix F), but interviews
varied depending on the interests or concerns of the participants. In addition to interview
notes, interviews were audiotaped and transcribed, with the exception of one interview
(200 level BIO participant), for which audio data could not be recovered. For this
interview, extensive interview notes were used for analysis.
62 Course Observations and Professor Interviews
Observations and professor interviews served as secondary data sources. To
provide context for the core courses, I attended more than half of class sessions for both
200 and 400 level Human Biology core courses. Field notes were taken describing the
activities and atmosphere of classes attended, and all professors for these courses were
interviewed to further establish goals for SSI and perceptions of student progress. One
interview with both 200 level professors was audiotaped and transcribed. The director of
the program who taught the 400 level class consulted with me often and participated in
advising on the dissertation. In addition, copies of syllabi, assignments, and handouts
used in these classes were collected.
Data Collection for Reasoning and Perceptions of SSI
Decision Making Questionnaire (DMQ)
Participants took a modified version of the Decision Making Questionnaire (Bell
& Lederman, 2003) near the end of the spring semester. The questionnaire was developed
by Bell based on various resources and validated through review by an expert panel of
four science educators and two scientists, then final modifications were made. Science
and technology issues were chosen to represent real controversial issues in which citizens
may need to consider and interpret a great deal of evidence to make decisions.
Although this questionnaire was originally used several years ago, I selected it
because it was designed to measure socioscientific reasoning in adults. Also, the
scenarios and the science behind them were likely to be familiar to a general audience of
science students, so little time was needed to provide participants with background
information. The original questionnaire included scenarios of science and technology-
63 related controversial issues, including fetal tissue implantation, climate change, the
relationship between diet and cancer, and smoking. To reduce the time required of
participants, and because of the highly emotional nature of the topic, I chose to omit the
first scenario on fetal tissue implantation. Scenarios were followed by questions that
asked students to take yes or no positions and explain the factors influencing their
decisions.
SSI Portion of Interviews
In addition to the DMQ questionnaire, Bell & Lederman (2003) conducted
follow-up interviews with participants, where they asked probing questions to validate
questionnaire responses and evaluate reasoning strategies. I used or adapted these
questions to further probe reasoning in each of the three scenarios (see Appendix F), and
asked clarifying questions about student responses on the DMQ. Follow-up questions
specifically asked how participants made decisions in response to opposing arguments,
which were still debated at the time of the interview.
Data Analysis for Reasoning and Perceptions of SSI
The modified DMQ was analyzed blindly to groups. “Yes,” “no,” and
“undecided” decisions for each question were totaled for the four groups and compared
by percentages of students choosing each decision. Differences in decisions between SSI
and BIO students were tested for significance using Fisher’s Exact tests for 200 level,
400 level, and total groups. Since undecided decisions were few, they were omitted from
the analysis.
64 Comparison of Factors in Decision-Making
Based on the entire set of unidentified DMQ responses, categories of factors
considered in decision-making for each question were established through several rounds
of development and revision. As similar themes in these factors emerged, category codes
were developed, refined, and used to re-code questionnaire responses. After I refined and
reduced the codes, a second researcher confirmed these codes or suggested adjustments
to the coding scheme, based on her analysis of an approximate 20% sample of
questionnaires (20 questionnaires). Finally, I reviewed all questionnaire responses and
adjusted coding to accommodate those small adjustments.
Since clusters of questions in the DMQ received similar responses in factors
considered, questions were grouped into emergent clusters that differed slightly from
grouping of questions by scenario. For each cluster, a list of “reasoning categories” was
developed and refined from the codes designated for the respective questions. For each
questionnaire, reasoning categories represented at least once in each cluster were
determined. Coded questionnaires were then identified by year and major, and the
number of students citing each reasoning category were compared for groups by
calculating percentages.
Development of Reasoning Rubric
To assess reasoning with SSI, a scale was adapted from Zohar’s and Nemet’s
(2002) argument analysis, and Tal and Hochberg’s (2000) Reasoning Complexity Rubric
originally developed from Hogan, Nastasi, & Pressley, (2000). The simplified scale
included number and explanation of justifications (see Tables 2 and 3). Like both cited
analyses, the rubric rated responses on number of justifications supporting their decisions
65 as well as whether students explained an underlying reason or mechanism for their
justifications (Tal & Hochberg, 2000; Zohar & Nemet, 2002). No points were awarded
when no reason was cited or the reason was nonsensical in the context of the question,
one point was awarded for one unelaborated or unexplained justification, two points were
given for two or more unelaborated justifications, three points were given for one
elaborated justification, four points were given for multiple justifications with one
elaboration, and five points were given for multiple elaborated justifications.
Table 2
Rubric for reasoning and perspectives applied to DMQ
Reasoning Score (R)
0-
1-
2-
3-
4-
5-
No
justification/nonsensica
l in context of question
One justification of
decision: mechanism
unelaborated
Two or more
justifications of
decision: mechanisms
unelaborated
One justification of
decision: mechanism
explained with
examples
Two or more
justifications of
decision: one
mechanism explained
Two or more
justifications of
decision: multiple
mechanisms explained
Perspectives Score (P)
Example: Ban Smoking?
0- No evidence of
multiple perspectives
1- Recognizes other
perspectives exist,
but does not elaborate
them.
2- Elaborates on
different
perspectives, but
offers no logical
conceptual resolution.
3- Considers different
perspectives in depth
and reaches a clear,
complex resolution
No…tobacco companies are
right in saying that smoking is
a free choice of the consumer.
However, it is not the free
choice of the nonsmoker
receiving passive cigarette
smoke. So, though cigarette
smoking should not be illegal,
there should, however, be
legislation passed that
confines cigarette smoking
only to smokers.
R: 4; Two reasons support
decision: free choice and
reasonable alternative
(explained)
P: 3; Resolution incorporates
perspectives of smokers,
tobacco companies, and nonsmokers
66 Table 3
Examples of scoring for reasoning scale.
Score
Participant Response
Explanation for scoring
1
No, that would have a negative effect on the
economy
One unelaborated
justification.
2
Yes, I do not like cigarette smoke in general, and
children seem to be starting smoking earlier and
earlier--it is very sad.
Two separate
unelaborated
justifications (personal
dislike, children
smoking)
3
I would be willing to pay increased taxes to
provide funding for research on alternative energy
resources because in the end by being more
efficient and less dependent on foreign oil I will
save money.
One justification is
explained.
4
Yes, I believe that more money should be given to
this research and IMPLEMENTATION. It is
already understood how solar and wind work, but
they must be implemented! We must be a leader in
the fight on global warming, demonstrating that
this issue is at the forefront of our concerns.
Two justifications given
(focus on implementation
and example for world).
Implementation is
elaborated, but why the
US needs to lead is not.
5
No [do not make smoking illegal]. With as much
information about the risks of smoking available
today, people should be responsible enough to
educate themselves and make their own decisions
about smoking. I do however think that smoking in
public areas should be illegal because then you are
exposing others to danger.
Two justifications are
given for the position
(keep smoking legal, but
not in public areas). Each
justification is explained.
67 Table 4
Examples of scoring for perspectives scale
Score
Participant Response
Explanation for scoring
0
I would be ok with this [tax increases to fund
alternative energy] because these techniques are
much better for our environment.
Only one perspective is
evident
1
Yes, people who choose not to smoke should not be
put in danger by those who choose to smoke. There
should be a special place designated for smokers
because they chose to live an unhealthy lifestyle.
Recognizes the position
of “those who choose to
smoke,” but does not
fairly consider this point
of view
2
It should because people that smoke are putting
themselves at risk for many types of cancer and
diseases. This in turn increases the cost of
healthcare that will have to be provided because of
their smoking. However, it also is someone's
decision or not to smoke, and you can't really pass
legislation against it because they have the liberty to
do it, even though it is extremely harmful.
Expresses health value
of legislation, but also
recognizes the
individual’s control over
health. However, no
resolution is reached.
3
On a personal level I believe they should [set limits
on emissions], though I do see reasons for not doing
so. The united states competes in the global market
with nearly every country on earth, and if one
country uses methods that are cheaper, though cause
more pollutants and greenhouse gasses, they are
more likely to perform better economically due to
their ability to produce the product at less of a cost
for the present (though long term these often will
cost us more). If a legally-binding limit can be
reached, I do think the united states however, as one
of the more powerful nations, has somewhat of an
obligation to do its best in complying with whatever
may be better for the future of mankind.
Explains and offers
examples for reasons for
supporting and nonsupporting positions. A
resolution is reached
where the influence of
the US is seen as an
adequate reason to
commit despite the
drawbacks.
Since multiple perspectives were commonly cited in questionnaires, though not
explicitly elicited by the DMQ, a perspectives score was adapted from the “synthesis”
component of the Reasoning Complexity Rubric (Tal & Hochberg, 2000). Since
68 inclusion of multiple perspectives was generally not in-depth due to the short nature of
responses, a simplified 3-point scale was used. No points were given if the participant
discussed only one perspective, one point was awarded when another perspective was
recognized, two points were given when another perspective was elaborated, but not
resolved with the perspective guiding the decision, and three points were given when
multiple perspectives were elaborated and incorporated into a resolution consistent with
the decision (see Tables 2 and 4).
The scoring rubric was reviewed for validity by the advising faculty member and
the researcher completing secondary coding. I analyzed the whole DMQ data set and the
second coder independently analyzed an approximate 20% sample (20 questionnaires).
Analysis was conducted blind to groups. Inter-rater reliabilities based on a 20% sample
were 78% for reasoning and 85% for perspectives. Discrepancies were resolved to reach
100% agreement and the remainder of the sample was then revised for consistency.
Average reasoning scores were computed for each student, and independent-samples ttests were conducted to compare SSI and BIO group totals. Data for average perspectives
scores were skewed toward the lower end of the scale, so I used a Mann-Whitney test for
non-parametric data for this scale.
Interview Analysis
Qualitative questionnaire data and interview transcripts were triangulated to
enhance validity of interpretations. Analysis of DMQ follow-up questions from Bell and
Lederman (2003) was guided by themes developed from King and Kitchener’s Reflective
Judgment Model (1994), with insights from Sadler, Barab, and Scott (2007), including
view of knowledge, recognition of complexity, consideration of perspectives, and use of
69 evidence (see Table 5). Student responses to the three follow-up questions were assessed
using the criteria described in Table 5. SSI and BIO participants were then compared
across groups. Responses to general questions about experiences with SSI were compared
within groups for emergent themes, then compared across groups.
Table 5
Assessment themes for stages of reflective judgment
Theme
Pre-reflective
Quasi-reflective
View of
knowledge
Complexity
Absolute, authority
driven
Not perceived
Uncertain, contextual
Tentative and inquiry-based
Other
perspectives
Evidence
Unrecognized
Perceived, frustrated with
ambiguity
Contextual nature
complicates evaluation
Used idiosyncratically in
reasoning
Understood, criteria applied
for evaluation
Considered across contexts
Not considered; truth is
directly observable
Reflective
Evaluated by criteria,
applied in context
Data Collection for Understanding of Scientific Inquiry
Views of Scientific Inquiry (VOSI) Questionnaire
The second section of the questionnaire included seven questions from the
“Views of Scientific Inquiry” (VOSI) questionnaire (Schwartz, Lederman, & Lederman,
2008), which measures students’ understanding of the inquiry process. I chose to use
questions from versions used with pre-service and in-service teachers and high school
students. I considered these versions, rather than the scientist version (VOSI-Sci) most
appropriate for college science majors, since most do not have experience with science
outside of the classroom context. In addition, one question from the Views of the Nature
of Science questionnaire (VNOS, Lederman, Abd-El-Khalick, Bell, & Schwartz, 2002),
was included to probe students’ understanding of theory and tentativeness in science.
The VOSI was developed to investigate participants’ understanding in the
70 following concepts: 1) scientific investigations are guided by questions, 2) scientists use
multiple methods, 3) there are multiple purposes driving investigations, 4) scientists must
justify scientific knowledge, 5) scientists must recognize and manage anomalous data, 6)
data and evidence are different, and 7) scientists work in communities of practice. Due to
time constraints, I included only seven questions from VOSI (see Appendix D). The
focus concepts often overlapped between questions, so these were coded in groups to
elucidate students’ understandings of these concepts.
I chose this open-ended instrument to assess student responses about the nature of
scientific inquiry. The inquiry process is central to the disciplines of biology as well as
the social sciences. This questionnaire asks students to reflect on the meaning of inquiry
and what scientists do as individuals and as a community. A reflective approach to
content and process is a key component of the Human Biology program, and as Boix
Mansilla and Duraising (2007) assert, reflection on the roles and integration of disciplines
is a criterion for quality interdisciplinary work. Thompson Klein (2007) explains that
integration of disciplines allows “metacritical reflection.” This questionnaire was used to
probe whether SSI students have come to view scientific inquiry differently from those in
a traditional program.
Inquiry Portion of Interview
The majority of this segment of the interview involved asking students to explain
or clarify their responses to questions on the modified VOSI. Participants were asked to
explain their understanding of scientific inquiry and discuss how they developed that
understanding. Questions varied depending on students’ questionnaires, but most
71 participants were asked to explain their conceptions of experiments, data/evidence, and
theories.
Data Analysis for Understanding of Scientific Inquiry
VOSI Analysis
Qualitative analysis questions began with initial coding of responses with targeted
concepts of the survey in mind. These included “processes of inquiry,” “meaning of
experiment,” “purpose of inquiry,” “definition or existence of scientific method,”
“difference between data and evidence,” “subjectivity” and “identification of anomaly”
(modified from start codes in Schwartz, 2004). The final question borrowed from the
VNOS (Lederman, Abd-El-Khalick, Bell, & Schwartz, 2002) assessed tentativeness of
science and definition of theory. Questions from all blinded questionnaires were coded in
groups that corresponded to focus concepts of the questions (see Appendix G) Emergent
codes were compiled throughout the initial analysis and after the first round, these codes
were reduced and revised. The questionnaires were then cyclically revised and recoded
until consistent. A graduate student familiar with the VOSI was consulted to review the
final coding scheme and suggestions were incorporated. After coding was complete,
questionnaires were divided into groups and codes were tallied for each group.
Percentages for each code were computed, since group size differed, and these were
compared across groups.
Analysis of Inquiry Portion of Interview
This portion of the interview was used primarily to ascertain the accuracy of my
interpretations of VOSI responses. I compared my initial interpretations of the VOSI to
student responses to probing and clarification questions and found answers to be
72 consistent. I also coded the inquiry portion of the text according to themes from interview
questions, including conceptions of inquiry, experiment, data and evidence, and theory. I
compared general codes among students within groups and across groups.
Data Collection for Levels and Perceptions of Biology Content Knowledge
Biology Concept Inventory (BCI)
Basic biology content knowledge was assessed using the Biology Concept
Inventory (BCI, Klymkowsky & Garvin-Doxas, 2008). The BCI was developed and
researched to measure content knowledge of central biology concepts and reveal
misconceptions. Distractor questions were based on common misconceptions and written
in students’ words from interviews conducted in the development of the BCI to reveal
students’ levels of understanding (D’Avanzo, 2008). The BCI was developed based on
responses of more than 500 college students to open-ended questions about biological
concepts. The major source of misconceptions revealed in the development of this tool
was students’ belief that random processes are very inefficient, while biological processes
are efficient, having some sort of “driver,” such as natural selection or concentration
gradients. Students did not understand the connection between constantly occurring
random processes and complex behaviors that emerge (Klymkowsky & Garvin-Doxas,
2008).
I chose the BCI to measure how students understood the major concepts in the
discipline of biology while targeting common misconceptions. Quality interdisciplinary
work demonstrates grounding in the disciplines employed (Boix Mansilla and Duraising,
2007), so students in both the Human Biology and biology majors should demonstrate
high levels of basic content knowledge. Since the concept inventory focuses on major
73 concepts in biology rather than detailed processes or vocabulary from biology subdisciplines, it should fairly assess students who have chosen different biology electives
and those who have not yet taken upper-level classes. The analysis should shed light on
whether Human Biology majors develop different levels of basic biology content
knowledge, since they invest a great deal of time considering social aspects of scientific
issues.
Perceptions of Content Knowledge Portion of Interview
As a part of the interview protocol for the 16 students interviewed, participants
were asked, “How would you describe your level of biology content knowledge after
completing (or at this point in) your major?” Students were then asked to respond to three
open-ended questions used in the development of the BCI to check whether student
misconceptions were consistent with those represented in the literature on the concept
inventory.
Data Analysis of Levels and Perceptions of Content Knowledge
BCI Analysis
Due to a communication error concerning the BCI software, a large portion of
BCI data could not be retrieved. Printed copies of the BCI were requested from students,
and fairly equivalent samples were obtained for each subgroup (15/30 from 200 level
BIO, 13/30 from 200 level SSI, 11/20 from 400 level BIO, and 13/15 from 400 level
SSI). Due to small sample size, a paired t-test was conducted to compare the means of the
total scores on the BCI between the Human Biology students and the biology students.
Analysis of Content Portion of Interview
74 Student responses to BCI validation questions were checked for consistency with
the assertions of the BCI developers, finding similar misconceptions in student responses
from both groups. All text concerning student perceptions of their content knowledge was
reviewed for emergent themes first in individual transcripts, then comparing within
subgroups and majors. Finally themes from SSI and BIO majors were compared to reveal
similarities and differences in perceptions.
Data Collection for General Perceptions of Major
Interview Data Collection
Within the semistructured interviews, students from both groups were asked to
talk about their perceptions of classroom learning environments in their majors. They
were asked about teaching strategies they found helpful and unhelpful, as well as how
they viewed levels of community and interaction with professors. They were directed to
speak primarily of courses within their major, but they were free to discuss experiences in
any of their courses. Participants were also asked if they had experienced non-traditional
teaching strategies, which deviated from a typical lecture format. Finally, students were
asked to talk about personal outcomes of their majors and what experiences, inside or
outside of normal major requirements were most significant in their development.
Analysis of General Major Perceptions
Text from the general perceptions segments of the interviews were coded
independently for major ideas and compared within groups for emergent themes. These
themes, supported with quotes and examples were compared and contrasted between SSI
and BIO groups.
75 Summary of Methods
In summary, I compare SSI and BIO groups in terms of socioscientific reasoning,
understanding of scientific inquiry, and levels and perceptions of content knowledge. In
addition I identify themes in students’ general perceptions of their majors. I use a mixed
methods convergence model of triangulation design (Creswell & Plano Clark, 2007)
comparing and contrasting various data sources including both qualitative and
quantitative data to develop interpretations (see Figure 1).
Note. Adapted from Creswell and Plano-Clark (2007).
76 CHAPTER 4: RESULTS
Socioscientific Reasoning and Perceptions of SSI
On eleven situational position-taking questions on the modified DMQ, SSI and
BIO groups were very similar in their responses (see Table 6). Decisions were compared
between groups for 200 and 400 level classes and total SSI and BIO students. According
to Fisher’s Exact probability tests of “yes” and “no” responses for SSI and BIO groups at
each level, the only significant difference was for question 8 in the 400 level class (SSI
60% yes, BIO 90% yes, p=.027). This question asked whether students exercised on a
regular basis, and differed from other questions in that it tested behavior rather than
reasoning. Although results were not significant, larger differences between groups were
seen for question 1, where BIO students were more likely to support legally binding
limits on carbon emissions (more pronounced at 200 level, 63% SSI vs. 87% BIO). Also,
BIO participants were more likely to answer “yes” to question 7, reporting that they were
likely to incorporate research into their decisions about what they eat (more pronounced
at 400-level, 33% SSI vs. 50% BIO). Finally, 400-level SSI participants were more likely
to answer “no,” (80% SSI vs. 50% BIO) to question 10, asking whether students thought
cigarette smoking should be made illegal.
77 Table 6
Percentages of SSI and BIO students by decision for questions on the modified DMQ
Question
numbers
Climate change
and policy
1
2
3
4
Health
research/food
choice
6
7
8
Regulation of
food or tobacco
9
10
11
12
Total
SSI
200/400
Yes
SSI
BIO
Total
200/400
BIO
Total
SSI
200/400
No
SSI
BIO
Total
200/400
BIO
Total
63/87
33/47
70/60
63/73
71
38
67
67
87/85
47/40
83/80
77/60
86
44
82
70
30/13
63/53
20/33
33/27
24
60
24
31
10/15
53/60
17/20
23/30
12
56
18
26
73/80
50/33
80/60
76
44
73
80/85
57/50
70/90
82
54
78
23/7
43/60
17/40
18
49
24
17/15
40/40
20/5
16
40
14
70/47
40/20
83/100
90/93
62
33
90
91
65
60/60
30/50
87/85
83/90
60
38
86
86
70
30/53
57/80
17/0
7/7
38
64
11
7
32
40/40
67/50
13/15
17/10
40
60
14
14
28
Comparison of Factors Influencing Reasoning
Through multiple rounds of coding, distinct categories were developed for factors
students indicated as influencing their reasoning in each of three clusters of questions.
These factors could be positively influencing their decision, negatively influencing it, or
simply brought up for consideration. In this comparison, the quality of reasoning is not
considered, but simply the types of factors mentioned. Questions from the DMQ were
clustered by similarity in responses. Ten categories were developed for the climate
change and policy cluster (questions 1-4), 9 categories were developed for the diet and
health research/food choice cluster (questions 5-9), and 11 categories were developed for
the regulation of food or tobacco cluster (questions 9-12).
78 For the climate change and policy cluster, factor categories included any reference
to the environment, evidence related to global warming, the need to keep individuals or
nations accountable for their role in climate change, the political influence the US has in
the world, influence of decisions on public perception of the US, personal values or
responsibility, political views, practical outcomes of decisions, suggestions of alternative
options to those suggested in the DMQ, or economic aspects of decisions. For the diet
and health research/food choice cluster, factor categories included food and exercise
choices as part of general lifestyle, preferences unrelated to research, long-term effects
like disease prevention, limitations on time and resources, influence of personal
experiences (such as witnessing family member’s disease), knowledge of research,
unawareness of research, distrust of research, and ambivalence toward health knowledge
or research. For the regulation of food or tobacco cluster, factor categories included
health, scientific evidence, need or desire to remove the problem through regulation,
health as personal responsibility, moral or social concerns, personal preferences,
smoking/unhealthy foods being appropriate in some situations, the need to be consistent
(as comparing cigarettes with alcohol), economic concerns, practical concerns, and
alternatives to regulation.
In general, SSI and BIO participants cited similar factors as influencing their
reasoning (see Tables 7-9). Total SSI and BIO groups did not vary by more than 15% on
the frequency of citing individual factors within question clusters. They differed by less
than 10% on the majority of factors (24/30). However, SSI students cited more factors as
influencing their decisions, considering the percentage of students citing particular
factors is higher for the majority of categories (29/30).
79 Table 7
Factors influencing reasoning in Climate change and policy question cluster of DMQ
Factors
Environment
Evidence
Accountability
Political
influence
Public
perception
Personal
values
Political
views
Practical
outcomes
Other
options
Economic
%BIO2
(n=30)
%SSI2
(n=30)
SSI2BIO2 (%)
%BIO4
(n=20)
%SSI4
(n=15)
SSI4BIO4 (%)
%Total
BIO
%Total
SSI
SSI-BIO
Total
83.3
66.7
-16.7
50
33.3
16.7
70.0
55.6
-14.4
33.3
43.3
10
35
46.7
11.7
34.0
44.4
10.5
23.3
43.3
20
40
26.7
13.3
30.0
37.8
7.8
33.3
13.3
-20
35
46.7
11.7
34.0
24.4
-9.5
6.7
23.3
16.7
25
26.7
1.7
14.0
24.4
10.4
56.7
70
13.3
75
66.7
8.3
64.0
68.9
4.9
16.7
16.7
0
15
26.7
11.6
16.0
20.0
4.0
63.3
70
6.7
70
66.7
3.3
66.0
68.9
2.9
46.7
63.3
16.7
50
60
10
48.0
62.2
14.2
90
80
-10
80
80
0
86.0
80.0
-6.0
Table 8
Factors influencing reasoning in Diet and health research/food choice question cluster of
DMQ
Factors
Lifestyle
choice
Personal
preferences
Limitations
Long-term
effect
Personal
experience
Research
Unaware of
research
Distrust
research
Ambivalence
% BIO2
(n=30)
%SSI2
(n=30)
SSI2BIO2
(%)
% BIO4
(n=20)
%SSI4
(n=15)
SSI4-BIO4
(%)
83.3
90
6.7
100
93.3
-6.7
16.7
30
13.3
35
46.7
11.7
10
30
13.3
16.7
3.3
-13.3
20
25
26.7
33.3
6.7
8.3
16.7
20
3.3
5
20
15
40
13.3
33.3
10
-6.7
-3.3
20
5
26.7
0
6.7
-5
10
16.7
6.7
15
6.7
-8.3
3.3
6.7
0
13.3
13.33
3.3
80 %Total
BIO
%Total
SSI
SSIBIO
Total
90.0
91.1
1.1
24.0
14.0
35.6
17.8
11.5
3.8
28.0
22.2
-5.8
12.0
32.0
20.0
31.1
8.0
-0.9
10.0
6.7
-3.3
12.0
2.0
13.4
8.9
1.4
6.9
Table 9
Factors influencing reasoning in Regulation of food or tobacco question cluster of DMQ
% BIO2
(n=30)
Factors
Health
Evidence
Remove
problem
Personal
responsibility
Moral/Social
Personal
Preferences
Appropriate
sometimes
Consistency
Economic
Practical
concerns
Other
options
%SSI2
(n=30)
SSI2-BIO2
(%)
% BIO4
(n=20)
%SSI4
(n=15)
SSI4BIO4 (%)
%Total
BIO
%Total
SSI
36.7
6.7
40
20
3.3
13.3
35
20
26.7
20
-8.3
0
36.0
12.0
35.6
20.0
SSIBIO
Total
-0.5
8.0
63.3
53.3
-10
35
73.3
38.3
52.0
60.0
8.0
70
56.7
-13.3
40
73.3
33.3
58.0
62.2
4.2
76.7
6.7
90
13.3
13.3
6.7
100
10
86.7
20
-13.3
10
86.0
88.9
2.9
8.0
15.5
7.5
0
13.3
13.3
25
13.3
-11.7
6.7
23.3
26.7
13.3
20
-10
10
10
6.7
20
-3.3
10
10.0
8.0
18.0
13.3
20.0
15.5
3.3
12.0
-2.4
33.3
23.3
-10
55
60
5
42.0
35.5
-6.4
50
40
-10
35
66.7
31.7
44.0
48.9
4.9
Differences of more than 10% between total SSI and BIO groups were found for
four reason categories. In the global warming question cluster, SSI students were more
likely to discuss alternatives to legislation (62% vs. 48%), refer to public perception of
U.S. (24% vs. 10%), and refer to evidence (44% vs. 34%), but were less likely to include
environmental factors in their decisions (56% vs. 70%). In the diet and health
research/food choice cluster, SSI participants were more likely to report that they make
food and exercise choices according to personal preferences or tastes (35% vs. 24%).
In the regulation of food and tobacco cluster, SSI students were more likely to
discuss consistency with other laws as influencing their reasoning (20% vs. 8%).
Although the difference for total groups was smaller, 400 level SSI students were much
more likely than BIO participants to cite availability of other options, like banning
smoking in public places, and the importance of personal responsibility as reasons why
smoking should not be banned (67% SSI vs. 35% BIO). They were also more likely to
81 discuss legislation of unhealthy foods or tobacco as a way to remove the problem (73%
vs. 35%).
Comparison of Reasoning
Using an independent samples t-test, mean reasoning scores were found to be
significantly higher for SSI students (M=3.46, SD=.63) than for BIO students (M=3.19,
SD=.68), t(93)= -1.98, p=.05; (see Table 10). For both SSI and BIO groups, reasoning
scores were higher for 400 level groups by about .2 points on the 5-point scale.
Table 10
Reasoning scores for SSI and BIO groups
200 level
Bio
SSI
(n=30) (n=30)
Reasoning Mean
3.10
3.40
Reasoning St. Dev. .66
.61
*p< .05
400 level
Bio
SSI
(n=20)
(n=15)
3.33
3.58
.70
.67
Bio
(n=50)
3.19
.68
Total
SSI
(n=45)
3.46
.63
Sig.
.050*
For perspectives scores, although the SSI mean (M=1.24, SD=.71) was slightly
higher than the BIO mean (M=1.04, SD=.57) no significant difference was found
between groups according to a Mann-Whitney test for non-parametric data (See Table
11). Still, it is worth noting that although the number of DMQ items in which participant
responses included any reference to multiple perspectives was nearly equal between
groups (SSI mean= 3.9; BIO mean= 3.8), of these responses, SSI students scored a higher
percentage of scores of 3 (55% vs. 47%), and lower percentage of scores of 1 (34% vs.
43%).
82 Table 11
Perspectives scores for SSI and BIO groups
200 level
Perspectives Mean
Perspectives St. Dev
*p<.05
Bio
(n=30)
.93
.54
SSI
(n=30)
1.10
.67
400 level
Bio
(n=20)
1.06
.59
SSI
(n=15)
1.26
.73
Total
Bio
(n=50)
1.04
.57
SSI
Sig.
(n=45)
1.24
.154
.71
Comparison of Reasoning in DMQ Follow-up Questions
In interviews and surveys, the majority of both SSI and BIO students’ responses
to scenarios were consistent with King and Kitchener’s (1994) reflective stages. Students
from both groups viewed knowledge as uncertain, tentative and inquiry-based, except
two SSI and two BIO students who suggested there was a single “best” answer. All
students perceived complexity of problems with only one BIO student hindered by it. All
students considered alternate perspectives across contexts, except one BIO student who
had difficulty resolving them. The majority of students in both groups sought resolutions
by recognizing similarities in different perspectives, for example, using their biological
knowledge to combine theories of carbon emissions and deforestation in contributing to
climate change. All students except one BIO student discussed applying criteria to
logically evaluate evidence. For example, most students said that to persuade them make
dietary changes, claims must have accumulated a great deal of long-standing evidence.
83 Perceptions of SSI in Majors
Views of SSI Students
All SSI students interviewed mentioned that they highly valued incorporation of
social aspects of biology-related problems in Human Biology. Gary described the major
as follows:
…the premise of our written assignments were to not only include the
biology or the physiology or the science aspect of what is going on in
these problems [controversial issues], but also to discuss the social
implications, whether it’s a good or a bad thing, what views are held, if we
accept the view, what would that change about society, things like that.
And so it’s almost like the core of the major is actually to focus on these
things. Not simply what is the science, but how does it affect people and
why is that important?
Sarah contrasted Human Biology courses with traditional biology courses:
Because a regular biology class would be like, oh, this is what a retrovirus
does, like AIDS. Well, now in this class, we’re learning all about AIDS,
what goes into it, how it affects the body more in-depth, how it affects the
social aspects, where in another class, we’re not really going to talk about,
like how people get treatment and how they (inaudible) funds or anything,
and that’s what we talked about in this class. So I feel like what we get is
more specific issues, but then within those issues it covers the whole range
of the issue.
All SSI students except one 400 level and one 200 level student noted that the
ability to consider multiple perspectives is important in science and health fields. Laura
cited a recent newspaper commentary arguing that academics had become too
specialized. “He said, you don’t have anyone in the world who understands the water
issue from every perspective. You have economists who understand it from that
perspective, you have politicians who understand it from that perspective, you have
people who are thirsty who understand it from that perspective. He said, but you don’t
have anyone who can put it all together.” Laura argued that to solve eminent social and
84 ecological problems like water conservation, people need to be familiar with different
disciplinary perspectives. Kelly also referred to science careers, explaining that Human
Biology has helped her decide to pursue a degree in public health as well as medical
training. She said,
And I think that’s what Human Biology makes me realize is that, when a
patient comes through in the clinic, there are other things going on that
you don’t see, that you have to think about, like can the patient afford to
be in there, are they going to take their medications, there are so many
other things on the different levels that you have to consider, that you
don’t just consider as an MD.
Sarah related the importance of incorporating multiple perspectives to her current
volunteer work in a cancer center and a women’s shelter. “And it just reinforces how I
want to help people, all the issues that surround, the social issues that we talked about in
class, I experience that now.” Despite the value she placed on considering multiple
perspectives, one student voiced concern that this training would not be valued in
professional school or the workplace. Laura said, “I’m worried that I’m going to
encounter people who are not interdisciplinary and people who are very rigid scientists
and they aren’t going to be able to appreciate the sociology.” She felt that the program’s
focus on integrating disciplinary perspectives was not yet common or accepted in
professional programs SSI students plan to enter.
All SSI students also said that they valued exposure to new ideas or controversies.
Several students mentioned that Human Biology core courses illuminated controversy in
issues they had never seen as problematic. For example, Laura said, “I didn’t know that
there was going to be a water crisis until we studied it in [the 400 level core course].”
Shawna said, “I guess it kind of made me realize how controversial some things are that
85 I’ve already had pretty opinionated stances on.” She said she became more willing to reevaluate her positions in light of new information and perspectives. Kelly said,
Some of [the issues], I think, you didn’t even know were controversial.
Like, I mean, to certain things, like the AIDS case we just studied, so it’s
like you know, I never knew that anybody believed that HIV [doesn’t
cause] AIDS, I never knew that. So I think that’s one of the biggest
advantages of Human Biology is that they raise awareness about the
controversy that does exist, and how different perspectives like on the
same issue, get completely different results. Or what people believe is
completely different.
Views of BIO Students
When asked how well prepared they believed they were to make decisions on
science issues with social implications, all BIO students said that they had little
experience with SSI in traditional science classes they had taken. Polly said,
In terms of just the biology classes I don’t think that they have prepared
me very well to have a stand because teachers usually, if they do bring up
controversial topics…right now I’m thinking about stem cell research, um
so I’m really interested in that, but the bulk of knowledge I do have about
that is outside of the classroom. And I took cell biology where they like
touched on it, but I mean not into the amount of detail that one would need
to have a stand.
In addition, all BIO participants felt that their biology courses focused primarily
on mechanisms. They felt it was left to the student to connect social aspects or alternative
perspectives. Ellen said, “I think they’ve kind of created those opportunities with the
genetics and the molecular biologies to, um, understand the mechanisms behind this, but I
think it’s left upon the individual to like search for those answers [to social problems] in
other disciplines or in the same disciplines in other fields...” Tracy said that such issues
had been briefly addressed in her biology classes, but she hadn’t had opportunities to
explore them in depth. The professor gave “just the overall result, what we learned from
86 it and move on.” When asked if she had had opportunities to integrate perspectives on
socioscientific issues in her courses, Carrie said, “I would probably say no. I mean, they
pretty much all focus in their own area. They never really connect to each other,
explicitly. I’ve never really thought about it that much either.”
Although all BIO students were interested in considering the social implications
of biological issues, one student felt that students would resist in-depth discussion of SSI
in biology courses. Kevin said,
On one degree I can see why it would be really good for them to teach us
that…but honestly I can see how they make it optional. Just because, even
for biologists, we have a lot of people who have hard core believes that
have been raised since childhood… And so I can see how a university
would try to distance themselves from offering something that would just
cause a flare up or something. It’s not quite the 70s anymore but you still
watch out.
Although they had few experiences discussing SSI in their biology courses, all
BIO participants said they had taken classes that explored social aspects of scientific
issues to some degree. These courses included anthropology and human genetics, medical
sociology, psychology, and religion and evolution. Approaches to studying issues in these
courses varied. Some students (2 of 4 who discussed this) felt those courses focused on
social aspects and expected knowledge on or generalized the biology content. Carrie said
of her medical sociology course,
I think that most of the students in that class were like premed or predental
or whatnot, so I think that they probably assumed that you have some
biological background, but, we never really got into anything really
science, it was more like issues that, like people who were going into the
sciences, particularly medical careers and how those related to
sociological aspects of how we live.
Some students (2 of 4 who discussed the issue) said that their courses focused on both
biological concepts and social implications. Tracy said, “Yes, it [anthropology and
87 human genetics] was about 60/40 [science/social issues]. [The professor] provided a book
that was optional, like a genetics dictionary, and it is a 2-day a week class, so the first day
she would have a lecture about the topic, so we wouldn’t be in the dark. And the next
day we would discuss.”
Despite having little SSI integrated into biology courses, half of BIO participants
at both levels reported feeling more able to make well-formed arguments with SSI. These
students integrated their knowledge from science and social science courses to consider
particular issues in depth. Kevin explained that the emphasis on supporting ideas with
evidence in the biology major helped him to reason more effectively with SSI. “Honestly
I think my major helped me argue this stuff a lot. Which is good, it gave me a way to
[use] my evidence and support my theories with it, in all honesty, supported from a
logical view, whether than being too emotional about one of my ideas.” Tracy attributed
her ability to argue for a position in SSI to her anthropology courses. She said,
I thought at the beginning when you said that a lot of students are tripped
up by the first questions [from DMQ] was interesting because I know for a
fact that if I didn’t have a lot of my anthropological classes, I would get
tripped up on those. But since I’ve applied them, and have to explain
them over and over again, it’s like I have a deeper understanding, whether
they are correct or not, of being able to sit with someone and explain the
effect to them. And then, I love the smoking example, because it’s
definitely something I’ve thought about and I just, I was very excited to
write about what I thought.
Overall, BIO participants expressed concern about SSI and found ways to apply their
biological knowledge to such problems.
88 Understanding of Inquiry
Modified Views of Scientific Inquiry Questionnaire
Emergent codes from the modified VOSI questionnaires were reduced and tallied
by groups (see coding scheme in Appendix G) Percentages of participants citing codes
for each question are included in Tables 12-25. A code was included in the tables only if
at least 5% of the total SSI or BIO groups cited that code.
Processes and Purposes of Inquiry.
Question 1 asked, “What types of activities do scientists do to learn about the
natural world? Be specific about how they go about their work” (see Table 12). SSI
students were more likely to indicate that scientists could participate in either natural
sciences or social sciences (22% vs. 8%), refer to the scientific method in their responses
(36% vs. 20%), and indicate that inquiry begins with a question (47% vs. 36%). BIO
participants were more likely to discuss a purely experimental view of science (38% vs.
22%) and discuss process skills of science, such as hypothesizing and collecting and
analyzing data (80% vs. 69%).
89 Table 12
Codes for VOSI Question 1
Code
%SSI2
%BIO2
%SSI2%BIO2
%SSI4
%BIO4
DIFF
METHODS
56.67
40.00
16.67
40.00
45.00
-5.00
51.11
42.00
9.11
SCIENTIFIC
METHOD
26.67
20.00
6.67
53.33
20.00
33.33
35.56
20.00
15.56
DIFF
SCIENCES
20.00
6.67
13.33
26.67
10.00
16.67
22.22
8.00
14.22
QUES
36.67
43.33
-6.67
66.67
25.00
41.67
46.67
36.00
10.67
CONTROL
13.33
10.00
3.33
13.33
10.00
3.33
13.33
10.00
3.33
EXPERIMENTAL
20.00
33.33
-13.33
26.67
45.00
-18.33
22.22
38.00
-15.78
PROCESSES
66.67
73.33
-6.67
73.33
90.00
-16.67
68.89
80.00
-11.11
GENERAL
INQUIRY
13.33
13.33
0.00
0.00
5.00
-5.00
8.89
10.00
-1.11
%SSI4%BIO4
%SSI
%BIO
%SSI%BIO
Note. Question 1 asked, “What types of activities do scientists do to learn about the
natural world? Be specific about how they go about their work.”
Question 2 asked, “How do scientists decide what and how to investigate?” (see
Table 13). Responses were coded as internal, external, or practical concerns. Groups were
fairly consistent in the types of concerns they cited, although the BIO group was slightly
more likely to cite only internal concerns (18% vs. 11%) and the SSI group was slightly
more likely to cite all three types of concerns (29% vs. 22%). The SSI group was also
more likely to cite more than one type of concern (69% vs. 60%).
90 Table 13.
Codes for VOSI Question 2
Code
%SSI2
%BIO2
INTERNAL
10.00
13.33
EXTERNAL
10.00
INT/EXT
%SSI4
%BIO4
%SSI4%BIO4
-3.33
13.33
25.00
-11.67
11.11
18.00
-6.89
13.33
-3.33
0.00
5.00
-5.00
6.67
10.00
-3.33
36.67
36.67
0.00
26.67
15.00
11.67
33.33
28.00
5.33
6.67
16.67
-10.00
6.67
5.00
1.67
6.67
12.00
-5.33
ONE TYPE
23.33
26.67
13.33
26.67
10.00
0.00
40.00
13.33
35.00
30.00
5.00
-16.67
28.89
22.22
22.00
28.00
6.89
-5.78
MORE
THAN ONE
TYPE
66.67
63.33
3.33
73.33
55.00
18.33
68.89
60.00
8.89
INT/PRACT
INT/EXT/
PRACT
%SSI2%BIO2
%SSI
%BIO
%SSI%BIO
Note. Question 2 asked, “How do scientists decide what and how to investigate? Describe
all the factors you think influence the work of scientists. Be as specific as possible.”
Meaning of Experiment
Question 3 asked participants to “Write a definition of a scientific experiment”
(see Tables 14-16). BIO participants were more likely than SSI participants to include
testing of a hypothesis (74% vs. 60%) and ensuring validity or precision of experiments
(18% vs. 7%). When asked, “Give an example from something you have done or heard
about in science that illustrates your definition of a scientific experiment,” BIO
participants were more likely to discuss an experiment conducted in a research lab or by a
research team (28% vs. 11%). They were also slightly more likely to give an explanation
why the example they described was an experiment that was consistent with their
definition of experiment. (82% vs 76%).
91 Table 14
Codes for VOSI Question 3a
Code
%SSI 2
%BIO2
%SSI2%BIO2
%SSI4
%BIO4
%SSI4%BIO4
%SSI
%BIO
%SSI%BIO
REPLICABLE
13.33
13.33
0.00
26.67
10.00
16.67
17.78
12.00
5.78
SCIENTIFIC
METHOD
16.67
16.67
0.00
20.00
0.00
20.00
17.78
10.00
7.78
TESTS HYPOTHESIS
60.00
70.00
-10.00
60.00
80.00
-20.00
60.00
74.00
-14.00
6.67
20.00
-13.33
6.67
15.00
-8.33
6.67
18.00
-11.33
CONTROLLED
30.00
26.67
3.33
26.67
20.00
6.67
28.89
24.00
4.89
GENERAL
INQUIRY
26.67
20.00
6.67
13.33
15.00
-1.67
22.22
18.00
4.22
VALID/
PRECISE
Note. Question 3a asked, “Write a definition of a scientific experiment. A scientific
experiment is…”
Table 15
Codes for VOSI Question 3b
Code
%SSI2
%BIO2
%SSI2%BIO2
%SSI4
%BIO4
%SSI4%BIO4
%SSI
%BIO
%SSI%BIO
RESEARCH
GROUP
10.00
30.00
-20.00
13.33
25.00
-11.67
11.11
28.00
-16.89
WHOLE
PROJECT
20.00
13.33
6.67
20.00
20.00
0.00
20.00
16.00
4.00
CLASS
46.67
46.67
0.00
46.67
35.00
11.67
46.67
42.00
4.67
SOCIAL
SCIENCE
10.00
3.33
6.67
6.67
10.00
-3.33
8.89
6.00
2.89
Note. Question 3b asked, “Give an example from something you have done or heard
about in science that illustrates your definition of a scientific experiment.
92 Table 16
Codes for VOSI Question 3c
Code
%SSI2
%BIO2
%SSI2%BIO2
%SSI4
%BIO4
%SSI4%BIO4
%SSI
%BIO
%SSI%BIO
CONSISTENT
80.00
76.67
3.33
66.67
90.00
-23.33
75.56
82.00
-6.44
INCONSIST
-ENT
16.67
16.67
0.00
33.33
10.00
23.33
22.22
14.00
8.22
Note. Question 3c asked, “Explain why you consider your example to be a scientific
experiment.”
Definition or Existence of the Scientific Method
When asked, “Is there one scientific method or set of steps that all investigations
must follow to be considered science?” SSI and BIO groups varied by only 3% in their
responses, where 69% of SSI students and 72% of BIO students responded “yes” (see
Tables 17-19). When asked to describe the steps of the method, SSI students were more
likely to include asking a question (49% vs 22%) and making observations (27% vs 8%).
BIO students were more likely to include hypothesizing (68% vs 23%) and analysis (40%
vs. 29%) in their responses. When those who answered that there was not one scientific
method were asked to “describe two investigations that follow different methods” and
“explain how the methods differ and how they can still be considered scientific,” 400
level SSI students were more likely to explain that social sciences may not invoke the
scientific method, but are still scientific (11% vs. 4%).
93 Table 17
Code
%SSI2
%BIO2
YES
70.00
76.67
%SSI2%BIO2
-6.67
NO
30.00
23.33
6.67
%SSI4
%BIO4
66.67
65.00
%SSI4%BIO4
1.67
33.33
35.00
-1.67
%SSI
%BIO
68.89
72.00
%SSI%BIO
-3.11
31.11
28.00
3.11
Note. Question 4a asked, “What do you think? Is there one scientific method or set of
steps that all investigations must follow to be considered science?”
Table 18
QUESTION
OBSERVAT
-ION
HYPOTHES
IS
ANALYSIS
COMMUNI
CATE
REVISE/
REPEAT
DATA
BG
RESEARCH
CONCLUSIONS
MAY
VARY
%SSI2
%BIO2
50.00
33.33
%SSI2%BIO2
16.67
30.00
10.00
60.00
%SSI4
%BIO4
46.67
5.00
%SSI4%BIO4
41.67
20.00
20.00
5.00
70.00
-10.00
40.00
26.67
40.00
-13.33
0.00
13.33
13.33
70.00
20.00
%SSI
%BIO
48.89
22.00
%SSI%BIO
26.89
15.00
26.67
8.00
18.67
65.00
-25.00
53.33
68.00
-14.67
33.33
40.00
-6.67
28.89
40.00
-11.11
-13.33
6.67
0.00
6.67
2.22
8.00
-5.78
23.33
70.00
20.00
-10.00
0.00
0.00
20.00
60.00
13.33
10.00
60.00
5.00
10.00
0.00
8.33
15.56
66.67
17.78
18.00
66.00
14.00
-2.44
0.67
3.78
60.00
56.67
3.33
46.67
55.00
-8.33
55.56
56.00
-0.44
6.67
3.33
3.33
0.00
10.00
-10.00
4.44
6.00
-1.56
Note. Question 4b asked, “If you think there is one scientific method, what are the steps
of this method?”
94 Table 19.
Codes for VOSI Question 4c
Code
%SSI2
%BIO2
%SSI2%BIO2
%BIO4
%SSI4%BIO4
6.67
6.67
0.00
20.00
0.00
20.00
11.11
4.00
7.11
CONTROL
16.67
0.00
16.67
6.67
25.00
-18.33
13.33
10.00
3.33
EXPLORE/
CONFIRM
3.33
10.00
-6.67
13.33
5.00
8.33
6.67
8.00
-1.33
DIFFERENT
METHODS
13.33
10.00
3.33
6.67
5.00
1.67
11.11
8.00
3.11
INVESTIGATE
6.67
6.67
0.00
6.67
15.00
-8.33
6.67
10.00
-3.33
SYSTEMAT
IC
6.67
0.00
6.67
6.67
5.00
1.67
6.67
2.00
4.67
DIFFERENT
SCIENCES
%SSI4
%SSI
%BIO
%SSI%BIO
Note. Question 4c asked, “If you think that scientific investigations can follow more than
one method, describe two investigations that follow different methods. Explain how the
methods differ and how they can still be considered scientific.”
Impact of Researcher on Science and Subjectivity.
When asked, “If several scientists, working independently, ask the same question
and follow the same procedures to collect data, will they necessarily come to the same
conclusions?” SSI students were only slightly more likely (93% vs. 86%) to say “no”
than BIO participants (see Table 20). They were more likely to cite error as a reason for
differences (47% vs. 30%), but BIO participants were more likely to cite different
interpretations of data (40% vs. 31%). When asked, “Does your response to (a) change if
the scientists are working together?” BIO participants were only slightly more likely to
respond that their answer would not change (62% vs. 58%, see Table 21). SSI students
more commonly responded that scientists would still be using different procedures (18%
vs. 4%), while BIO students were more likely to cite error (16% vs. 7%) or different
interpretations of scientists (28% vs. 20%).
95 Table 20
Code
%SSI2
%BIO2
%SSI2%BIO2
%SSI4
%BIO4
%SSI4%BIO4
%SSI
%BIO
%SSI%BIO
NO
96.67
86.67
10.00
86.67
85.00
1.67
93.33
86.00
7.33
ERROR
50.00
26.67
23.33
40.00
35.00
5.00
46.67
30.00
16.67
DIFFEENT
DATA
40.00
56.67
-16.67
53.33
30.00
23.33
44.44
46.00
-1.56
DIFFERENT
METHODS
23.33
6.67
16.67
6.67
35.00
-28.33
17.78
18.00
-0.22
DIFFERENT
INTERPRET
ATIONS
33.33
46.67
-13.33
26.67
30.00
-3.33
31.11
40.00
-8.89
CAN COME
CLOSE
10.00
3.33
6.67
6.67
0.00
6.67
8.89
2.00
6.89
YES
3.33
3.33
0.00
0.00
5.00
-5.00
2.22
4.00
-1.78
MAYBE
0.00
6.67
-6.67
13.33
10.00
3.33
4.44
8.00
-3.56
SAME
PROC/
DATA
0.00
3.33
-3.33
20.00
5.00
15.00
6.67
4.00
2.67
0.00
6.67
-6.67
0.00
10.00
-10.00
0.00
8.00
-8.00
DIFFERENT
INTERP
Note. Question 5a asked, “If you think there is one scientific method, what are the steps
of this method? If several scientists, working independently, ask the same question and
follow the same procedures to collect data, will they necessarily come to the same
conclusions? Explain why or why not.”
96 Table 21.
Code
%SSI2
%BIO2
%SSI2%BIO2
%SSI4
%BIO4
%SSI4%BIO4
%SSI
%BIO
%SSI%BIO
CHANGE
36.67
30.00
6.67
20.00
15.00
5.00
31.11
24.00
7.11
SAME
DATA
10.00
10.00
0.00
20.00
5.00
15.00
13.33
8.00
5.33
CONSENSUS
23.33
20.00
3.33
13.33
5.00
8.33
20.00
14.00
6.00
REDUCE
ERROR
10.00
3.33
6.67
0.00
10.00
-10.00
6.67
6.00
0.67
NO
CHANGE
53.33
60.00
-6.67
66.67
65.00
1.67
57.78
62.00
-4.22
DIFF.
METHODS
16.67
0.00
16.67
20.00
10.00
10.00
17.78
4.00
13.78
DIFF.
INTERP
20.00
33.33
-13.33
20.00
20.00
0.00
20.00
28.00
-8.00
DIFF.
DATA
10.00
3.33
6.67
13.33
15.00
-1.67
11.11
8.00
3.11
ERROR
3.33
16.67
-13.33
13.33
15.00
-1.67
6.67
16.00
-9.33
MORE
LIKELY
SAME
6.67
13.33
-6.67
6.67
15.00
-8.33
6.67
14.00
-7.33
MAYBE
CHANGE
10.00
10.00
0.00
13.33
20.00
-6.67
11.11
14.00
-2.89
SAME
PROC/
DATA
10.00
3.33
6.67
13.33
10.00
3.33
11.11
6.00
5.11
CONSENSUS
10.00
6.67
3.33
13.33
5.00
8.33
11.11
6.00
5.11
6.67
3.33
3.33
6.67
10.00
-3.33
6.67
6.00
0.67
DIFFERENT
INTERP.
Note. Question 5b asked, “Does your response to (a) change if the scientists are working
together? Explain.”
Difference Between Data and Evidence.
When asked, “What does the word “data” mean in science?” BIO participants
were more likely to define it as information collected in inquiry (90% vs. 73%), whereas
SSI participants often defined it as “results” (22% vs. 8%, see Table 22). When asked, “Is
‘data’ the same or different from ‘evidence’?” both groups responded “different” (89%
SSI and 86% BIO, see Table 23). BIO students were somewhat more likely to respond
97 that evidence is less precise or exact than data (12% vs. 4%), but many reported that it
was more certain or definitive than data (10% BIO vs. 4% SSI). SSI participants were
more likely to report that data can be evidence, but not explain how they are different
(11% vs. 2%) and to say that evidence is data that has been analyzed or interpreted (9%
vs. 2%).
Table 22
Code
%SSI2
%BIO2
%SSI2%BIO2
%SSI4
%BIO4
%SSI4%BIO4
%SSI
%BIO
INFO
COLLECTED
76.67
86.67
-10.00
66.67
95.00
-28.33
73.33
90.00
-16.67
RESULTS
23.33
10.00
13.33
20.00
5.00
15.00
22.22
8.00
14.22
NUMERIC
10.00
10.00
0.00
0.00
5.00
-5.00
6.67
8.00
-1.33
QUANT/
QUAL
10.00
13.33
-3.33
26.67
10.00
16.67
15.56
12.00
3.56
Note. Question 6a asked, “What does the word “data” mean in science?”
98 %SSI%BIO
Table 23
Code
%SSI
2
%BIO2
%SSI2%BIO2
%SSI4
%BIO4
DIFFER
EVIDENCE
SUPPORTS/
EVIDENCE
IS MORE
CERTAIN
EVIDENCE
IS LESS
PRECISE
86.67
86.67
0.00
93.33
85.00
8.33
88.89
86.00
2.89
56.67
46.67
10.00
33.33
65.00
-31.67
48.89
54.00
-5.11
3.33
13.33
-10.00
6.67
5.00
1.67
4.44
10.00
-5.56
6.67
6.67
0.00
0.00
20.00
-20.00
4.44
12.00
-7.56
3.33
3.33
0.00
13.33
5.00
8.33
6.67
4.00
2.67
6.67
6.67
0.00
6.67
5.00
1.67
6.67
6.00
0.67
10.00
3.33
6.67
13.33
0.00
13.33
11.11
2.00
9.11
6.67
13.33
0.00
13.33
6.67
0.00
13.33
6.67
5.00
10.00
8.33
-3.33
8.89
11.11
2.00
12.00
6.89
-0.89
10.00
13.33
-3.33
0.00
10.00
-10.00
6.67
12.00
-5.33
EV. IS
GENERALIZATION
DATA IS
NUMBERS
DATA CAN
BE
EVIDENCE
EVIDENCE
IS
ANALYZED
SAME
SUPPORT
%SSI4%BIO4
%SSI
%BIO
%SSI%BIO
Note. Question 6b asked, “Is “data” the same or different from “evidence”? Explain.”
Methods of Data Analysis
When asked, “What is ‘data analysis’?” and “What is involved in doing data
analysis?” both groups most commonly cited interpretation or making meaning of data
(89% SSI and 96% BIO, see Tables 24). SSI participants were much more likely to
include visualizing data through graphs or charts (29% vs. 14%) and checking validity or
accuracy of data collection (22% vs. 6%). They also included using statistics more (40%
vs. 30%) and compiling and reviewing data (16% vs. 6%). Both groups showed marked
differences between 200 and 400 levels in inclusion of statistical tests (SSI increasing
50% and BIO increasing 42%) and finding patterns in data (SSI increasing 17% and BIO
increasing 20%).
99 Table 24
Codes for VOSI question 7
Code
%SSI2
%BIO2
VISUALIZE
26.67
13.33
%SSI2%BIO2
13.33
CHECK
VALIDITY/
ERROR
30.00
6.67
INTERPRET
86.67
COMPARE
%SSI4
%BIO4
33.33
15.00
%SSI4%BIO4
18.33
23.33
6.67
5.00
96.67
-10.00
93.33
10.00
16.67
-6.67
STATISTICS
23.33
13.33
ORGANIZE
16.67
REVIEW/
COMPILE
DATA
%SSI
%BIO
28.89
14.00
%SSI%BIO
14.89
1.67
22.22
6.00
16.22
95.00
-1.67
88.89
96.00
-7.11
26.67
5.00
21.67
15.56
12.00
3.56
10.00
73.33
55.00
18.33
40.00
30.00
10.00
20.00
-3.33
0.00
0.00
0.00
11.11
12.00
-0.89
23.33
10.00
13.33
0.00
0.00
0.00
15.56
6.00
9.56
REDUCE/TR
ANSFORM
10.00
6.67
3.33
0.00
0.00
0.00
6.67
4.00
2.67
PATTERNS
23.33
20.00
3.33
40.00
40.00
0.00
28.89
28.00
0.89
Note. Question 7 asked, “(a) What is “data analysis”? and (b) What is involved in doing
data analysis?”
Tentativeness of Theory and Purpose of Theory.
The final question asked, “After scientists have developed a theory, does the
theory ever change? If you believe that theories do change, explain why theories are still
important to the scientific community.” The majority of both groups responded “yes”
(98% SSI and 96% BIO, see Table 25). Both groups commonly reported that discovery or
availability of new data contributed to the tentativeness of theory (49% SSI and 46%
BIO), but BIO majors were more likely to discuss new technology as a catalyst for
change (16% vs. 7%). BIO majors were also more likely to discuss a falsification view of
changing theories, explaining that theories are put forth by scientists to be retested until
they are either disproven or withstand adequate attempts at falsification (26% vs. 8%).
100 Surprisingly, the BIO group was slightly more likely to cite new interpretations of
existing data (8% vs. 2%). Both groups commonly explained that theories were important
for generation of ideas for future inquiry (47% SSI and 42% BIO), but SSI students were
more likely to report that theories are needed for lively discussion within scientific
communities (16% vs. 8%). BIO majors were slightly more likely to explain that theories
are important to provide a record of scientific thinking over time (8% vs. 2%).
Table 25
Codes for questionnaire Question 8
Code
%SSI2
%BIO2
%SSI2%BIO2
%SSI4
%BIO4
%SSI4%BIO4
%SSI
%BIO
%SSI%BIO
96.67
96.67
0.00
100.00
95.00
5.00
97.78
96.00
1.78
43.33
36.67
6.67
60.00
60.00
0.00
48.89
46.00
2.89
6.67
13.33
-6.67
6.67
20.00
-13.33
6.67
16.00
-9.33
0.00
10.00
-10.00
6.67
5.00
1.67
2.22
8.00
-5.78
10.00
6.67
3.33
6.67
0.00
6.67
8.89
4.00
4.89
26.67
23.33
3.33
40.00
35.00
5.00
31.11
28.00
3.11
3.33
10.00
-6.67
0.00
0.00
0.00
2.22
6.00
-3.78
16.67
6.67
10.00
6.67
15.00
-8.33
13.33
10.00
3.33
10.00
30.00
-20.00
33.33
20.00
13.33
17.78
26.00
-8.22
46.67
46.67
0.00
46.67
35.00
11.67
46.67
42.00
4.67
16.67
6.67
10.00
13.33
10.00
3.33
15.56
8.00
7.56
3.33
6.67
-3.33
0.00
10.00
-10.00
2.22
8.00
-5.78
YES
NEW DATA
(NEW TECH)
NEW
INTERPRET
ATIONS
SCIENCE
CHANGES
BEST
CURRENT
EXPLANATION
THEORY
LESS TRUE
THAN LAW
FINAL
TRUTH
EXISTS
FALSIFICAT
-ION VIEW
IDEAS FOR
NEW
INQUIRY
PROMOTES
DISCUSSION
HISTORICAL RECORD
Note. Question 8 asked, “After scientists have developed a theory, does the theory ever
change? If you believe that theories do change, explain why theories are still important to
the scientific community. Defend your answer with examples.”
101 Inquiry Portion of Interviews
Definition of Inquiry
SSI group. For the SSI group, all the 400 level students and three of the 200 level
students defined inquiry as questioning and trying to understand or explain phenomena.
One 200 level student said inquiry was recognizing and solving a problem. Three 400
level students mentioned there were different ways of approaching inquiry, and one 200
level student said scientists needed to look at problems at different levels. Kelly said,
Like if you have a good hypothesis, you’re going to look at everything
from life style to the biology. You can’t just straight look at it, like the
blood pressure…it’s kind of like if you really want to get to the bottom of
the problem, you have to look at it from the lense of a biologist as well as
a sociologist…So yes, when you get to the testing, or the experimental
part of it, it should be everything from the actual, the way you think of it
as a laboratory experiment, to observing a person in their environment,
like their life style.
BIO group. Similarly, three of the 400 level BIO students and two of the 200 level
BIO students said inquiry was seeking to answer a question. One 400 level and one 200
level student said inquiry was solving a problem, and one 200 level student defined
inquiry by the processes of collecting and interpreting data.
Experiences Leading to Inquiry Understanding
SSI group. All of the 400 level SSI students mentioned an upper level physiology
class taught through the biology department by the director of Human Biology as having
a significant role in establishing their understanding of inquiry. Three 400 level and two
200 level SSI students referred to the Human Biology program in general as significant,
while one at each level cited research lab experience, one at each level cited everyday life
experiences, one 400 level student cited reading scientific literature, and one 200 level
student cited classes in general. In support of Human Biology, Gabrielle said,
102 I think the majority of where I learn this is Human Biology, just because,
and it’s not all biology based, like you have to look at different problems
thru the sociological perspective and so, but you still learn the scientific
method, you come up with a question, and you kind of try to figure out
what’s working or not and also I think it helps that we did a lot of research
especially in upper physiology, we did a lot of research and lab reports
that really prepared me for that.
Gary said, “I think actually, this is one thing I’m happy about, the Human Biology
program for…just the idea that, things like inquiry aren’t set to just one set of standards.
There isn’t just a lab procedure that someone gives to you, that you perform and you
write a lab report on. We’re asked to do our own investigation, things like that.”
BIO group. For the biology students, three 400 level and two 200 level students
said they gained their understanding of inquiry through classes (one of which included
social science classes), one 400 level and three 400 level students cited work in research
labs, two 400 level and one 200 level student cited K-12 science classes, two 400 level
students cited life or college in general (science is an intuitive or human process), and one
student cited interaction with scientists, influence of family members or listening to the
media.
Two BIO students related their experience in research labs very differently. Chloe
felt her lab experienced reinforced her previous learning on the scientific method. She
said,
I feel like kind of even in high school you learn about the scientific
method, stating your hypothesis, and all your variables and stuff like that.
You feel like you actually understand it and [the research lab] does help to
actually be in that environment. See it there on paper. Or try to
accomplish this. We’re going to do this experiment to figure it out. We’ll
do this data analysis to see the results.
Tracy felt that her class experiences taught her a different scientific method than
she experienced in the research lab.
103 Honestly, my only experience with anything to do with the scientific
method has to be in the labs I’ve taken and that would be chemistry labs
and those very, very much follow that guideline. They have the purpose
that you want to find, what you’re going to use, the fact that you need to
have a positive or a negative control, everything is along with what my
high school education has been, and in the classes where there aren’t any
labs, sure the professor will bring up and experiment but we don’t go into
the minute details of how it was conducted, we just get the results and
what it means to us.
Tracy felt that her science classes presented a prescriptive scientific method, offered
“cookbook” style lab experiences, and presented outcomes, not actual processes of
scientific research.
Definition of Experiment
SSI group. For SSI students, two of the 400 level and all of the 200 level students
defined “experiment” the same as “inquiry,” involving questioning and carrying out
various processes to reach conclusions. Only two 400 level students discussed
manipulating or controlling variables. For the 200 level SSI students, one understood
inquiry as the procedural part of the scientific method, and one was unable to define
experiment. Of three SSI students from each level asked to discuss the scientific method,
two 400 level and one 200 level students mentioned varied, “fluid,” or “circular”
enactment of steps. One 400 level and two 200 level students said there were different
methods of inquiry included in the scientific method. One said there is no scientific
method, arguing that clinical observation doesn’t fit the steps, but is still scientific.
BIO group. For the BIO group, two students from each level defined experiment
similar to inquiry in general, as a way to find answers or test a hypothesis. One 400 level
and two 200 level BIO students said that an experiment involved manipulating or
controlling variables (one mentioned inclusion of social science research), and two 200
104 level students said experiments could include naturalistic or observational studies. One
200 level student said experiments attempt to disprove something, while inquiry attempts
to answer a question. Two students at each level discussed the scientific method, where
one at each level described it as a general process of hypothesis testing and one at each
level mentioned varied orders of steps.
Understanding of Data and Evidence
SSI group. For SSI students, all 400 level and three 200 level students understood
that evidence differed from data in that it is used to “make a case “ for an assertion,
support or refute an assertion, or is interpreted from collected data. Dana said, “Data is
just what it is, it’s the calculations. And evidence is when you use data to try to persuade
someone to see a certain point of view, or to argue a point. Data can be used as evidence
to advocate for a certain drug or something that reduces the heart rate, or whatnot.” Three
400 level students were confused about whether data could be quantitative or qualitative,
and were inclined to see data as numbers. One SSI student from each level said that
evidence was more concrete or more “backed up,” showing confusion about the nature of
evidence.
BIO group. The BIO students had similar responses, where three from each level
understood that evidence supports a conclusion (although one defined data and evidence
as the same). One 400 level student said data is numbers, and one student from each level
thought evidence was more tangible, like evidence from a crime scene.
Definition of Theory
SSI group. All SSI students recognized theory as supported with evidence, but
most had misconceptions about the nature of scientific theory. All of the 400 level SSI
105 students and 2/3 of 200 level students who discussed theory viewed theory as less
evidence-backed than law or fact. Ben said, “I guess it’s like an opinion on why
something happens that hasn’t been proven yet. I would probably say it’s based on the
evidence that you collected at the best, like an explanation for something at the point, but
you can’t claim it’s 100% true…or accurate.” Shawna had a more informed
understanding of theory, saying “I guess it’s just basically a statement that you can make
once you have substantial evidence and research that backs up the claim. Generally I
guess accepted by the scientific community.”
BIO group. The BIO students also recognized that theories are supported with
evidence (all students), but varied greatly in their more specific definitions. Of the 400
level BIO students, one said a theory is the same as a law, a supported hypothesis that has
not yet disproven, one said it is a hypothesis no one has tried to dispute yet, and one said
it is a currently accepted idea. For the 200 level students, one said theory is the best
explanation but less substantiated than law, one said theory is a supported idea that
scientists try to disprove, one student described theories as “ideas of how things happen,”
and guidelines leading to new ideas, and one said theories are ideas that become
permanent with sufficient evidence. Overall, interviewed students saw theories as
evidence backed, although more SSI students referred to a hierarchy in which theory was
less backed than laws or facts.
BCI scores from a limited sample of 26 Human Biology majors and 26 biology
majors showed little difference between the two groups (see Table 26.) At each level and
106 in total, Human Biology and biology means varied by less than one question on the
concept inventory (SSI total M= 13.66, SD=3.29 and BIO M= 14.0, SD=3.25).
Table 26
BCI scores for SSI and BIO groups
Mean score (out
of 30 points)
Standard
Deviation
*p<.05
200 level
Bio
SSI
(n=15) (n=13)
13.20 12.23
400 level
Bio
SSI
(n=11) (n=13)
14.77
14.64
Bio
(n=26)
13.81
Total
SSI
(n=26)
13.50
3.00
3.19
3.25
3.29
2.98
3.53
Sig.
.736
Perceptions of Biology Content Knowledge Portion of Interview
All SSI students interviewed said they had a good understanding of the general
concepts of biology except one senior level student. However, two students mentioned
that their overall biology content knowledge was only average. Gary explained that
although his “big picture” knowledge was strong, he felt that more detailed knowledge
valued more highly, especially in standardized tests like the medical exam, the MCAT.
All SSI students also discussed how they were stronger in their areas of interest in
biology. These areas included anatomy and physiology, cellular mechanisms, and
epidemiology, subjects relevant to their future careers in medicine or health fields.
SSI Group
Three SSI students gauged their content knowledge according to their preparation
for the MCAT. Two students were confident relying on their premedical classes outside
of Human Biology to establish this content knowledge, while one senior student
expressed concern that too much time had passed since he took his premedical courses to
feel confident on the exam.
107 Three students responded that content knowledge was lacking in Human Biology
and they would like to see more detailed concepts incorporated into core courses. Gary
noted, “Of course, now I’m a senior, so I’m getting ready to take the MCATS and the
aptitude tests and part of that section is biology and I haven’t started to study and I am
somewhat apprehensive about the fact that I’m going to have to put more work into it
than I probably should as a Human Biology major necessarily.” Still, two of these
students recognized that with different student interests in Human Biology from medicine
to biology research to social science focuses, it would be difficult to accommodate all
students with an in-depth focus on biology concepts. Kelly said, “I guess it’s because I’m
really interested in the biological processes as well. So I would like to see more of a
balance of that, but, I don’t know how you avoid boring the people who already know all
of it, it’s hard because we’re from such different backgrounds.” Shawna noted that
Human Biology core courses could spur interest in areas of biology and offer
opportunities to independently gain content knowledge, although this work was not
required. She noted, “I guess a lot of times certain resources are provided as kind of a
gateway to look into that aspect of it more, but the way in which we’re tested in class, it
doesn’t require that you actually have a thorough understanding of the science.” Ben
noted that he gained most of his content knowledge through independent study, “like
reading the chapters and the assigned work,” in both biology and Human Biology
courses. He said, " Like with the Human Biology, I learned more because I feel obligated
to my group to make sure I know all of it,” stressing that resources for learning biology
content were provided and incentives to learn were emphasized through the team learning
structure.
108 Two of the 400 level SSI students commented that taking fewer upper level
biology courses was appropriate, since detailed content knowledge was not the sole focus
of their major. Dana said, “I think, like compared to the regular biology degree, I have a
different understanding of biology. I mean, I’ve taken like the actual biology courses like
[lists biology courses], but I feel like with Human Biology, you have to look at a broader
scale, so it’s more like an epidemiological perspective, the thing is, so I probably haven’t
focused as much on the cell, things like that.” They recognized that participation in the
program allowed them to choose how many upper level biology courses they would take.
BIO Group
BIO students generally gave shorter responses when asked about their perceptions
of their biology content knowledge. All students reported feeling comfortable with the
foundational concepts in biology. All except for two students reported feeling less
comfortable with more detailed concepts. Half of BIO students at each level mentioned
that they understood the biology curriculum as providing the “big picture” in early
classes and providing “details” in upper-level courses. Ellen explained, “I think more so
how they do it here is that they give you an overview and then through, like molecular
biology, genetics, what have you, microbiology, um, you can see the pieces that make the
whole.”
Two senior students noted that they felt more comfortable in areas where they had
taken more classes. Kevin felt strong in genetics and evolution because these concepts
were repeated throughout the curriculum and Carrie felt strong in evolution because she
had elected to take additional courses on evolution. Kevin felt that his strength in biology
content related directly to his experience in a research lab. He said, “I worked in a
109 molecular biology lab for the year before I took half these classes where I was actually
running the tests and running the labs, which I really believe the labs are the best for
me… Applying the process is what actually helped me.” For Kevin, lab experienced
reinforced his development of content knowledge.
Student Perceptions of Majors
Both SSI and BIO participants were interviewed to understand their perceptions
of four three general areas of their majors: personal outcomes, perceptions SSI in their
majors, and perceptions of the learning environment in their courses.
SSI Group
All SSI participants said they felt more able to consider multiple perspectives as a
result of participating in the program. Shawna explained, “I think it’s been good to see
both sides of things. I guess I’ve kind of gotten a little less opinionated in the sense that
I’m a little bit more open to other reasoning on that I never saw as logical before but I
guess I understand them better now.” Kelly elaborated on the pedagogical approach that
helped her develop this competency.
…AIDS, tuberculosis, everything, you looked at it all from like, from the
very miniscule bacteria to the entire city. Every level. So, I mean, I think
that’s one of the essential principals of Human Biology, is that you look.
You look at different viewpoints, like when you have a problem, not a
problem but anything that you have to bring into perspectives to really get
a feel or understanding of what’s going on.
All SSI students except one 200 level student reported feeling more able to
discuss controversial issues or take a position on such issues. Kelly said,
I’d say the overall goal is just making us question information we’ve been
given and evaluate our own things that are important to us, and to try to
really get out what you believe in. It’s helped me grow, having confidence
110 in doubting something. Like I guess before I kind of never even thought
to doubt stuff, like one professor told me is true, like what I learn in school
is true, and I’ve never been encouraged to doubt something.
Sarah said, “I just think, I have a broader outlook on things now when they’re presented
to me, instead of just like, oh this is what happens like this, when I can be like, oh well,
this [is an] issue that surrounds it and you have to think about what if this happened, and
contrast it.” Through discussion of SSI issues in core courses, students learned to
question information presented, and to explore different aspects of the issue.
Two 400 level SSI participants noted that they improved in making evidencebased arguments or were more willing to research issues. Gabrielle said, “I think I’m
more open and more, I’m willing to do more research to find, for me to pick a side, to
support my beliefs a little bit more, whereas before, I don’t agree with this, but I wouldn’t
really know why I wouldn’t agree, or take the time to see the opposing side, but no, my
way is the right way, kind of thing.” Dana said, “I’m able to formulate good arguments
and research other primary literature, like we’ve had to do that so much, that’s definitely
a big thing that I’m glad I’ve learned how to do for my future.
BIO Group
Three out of four BIO participants at each level considered discovering passions
in biology or biology-related professions as important outcomes of their majors. Ella
appreciated being exposed to “new and upcoming ideas.” Ellen said she gained a better
understanding of science and its “utility for the world.” Polly said [the biology major]
“has made me love science even more. Learning about it made me want to pursue my
goals, I guess.”
111 More than half of BIO participants (3/4 400 level and 2/4 200 level) said they
developed diligence or responsibility in their major. Kevin said, “It’s honestly, the main
thing it’s taught me to do is how to establish goals and meet them myself.” Polly said, “I
started out with not a very good idea of how to study for science classes, especially in
college it’s very different from in high school, so it took me a while to get used to it, but
once I did, I started liking the courses more and more. I tend to like things more if I know
them very well. So I’ve just developed in how best I learn.”
Two out of four of the 400 level BIO participants said they learned about the
challenges of scientific research or graduate school. Natalie said, “I think I’m more
realistic now about how hard it will be to do what I want to do… I mean, I’m still
optimistic, I’m not saying that someone who wants to do something shouldn’t, I’m just
more realistic about what I need to do and how it has to be done.” Ellen said, “This
major has helped me to see that things take time, and um, it has allowed me to see that
you’re not always going to have a direct result, sometimes, I don’t like this answer, but
more often you’re gonna fail than you succeed, and that’s in experiments as well, so and
the importance of diligence, so that’s what this has helped me to see.” She noted that her
experience in a research lab as well as in her classes helped her see that scientists must
learn to accept failure and frustration as part of their daily experience. After graduation,
she intended to gain more experience in a research lab to prepare her for the
psychological rigors of medical school. She said, “You need to be able to take it
mentally—deal with the stress.”
112 Perceptions of the Learning Environment
SSI Group
All SSI students interviewed valued the team-teaching approach. They
appreciated having experts from different disciplines model the integration of
perspectives to approach an issue. They also valued the accessibility of knowledgeable
teachers to help them apply complicated content knowledge. Dana said, “It’s interesting
how they have usually two teachers teaching together and like how, they had a
neuroscientist with a sociologist teaching together to just give you a lot of different
perspectives on disease… It’s very integrated and they try to give you as much different
backgrounds as possible.” Laura felt that integration of perspectives varied among her
core courses. She felt some professors were too attached to one disciplinary perspective
when dealing with issues, and this was an ineffective model for problem solving with
socioscientific issues.
The majority of SSI students (3/4 at both levels) said that they valued
collaborative work in their major. Laura said, “So they [core classes] are very team
based. And the rationale behind it has to do with the fact that when you get out into the
real world, 9 times out of 10, most jobs you’re going to be working in a team... In some
ways it’s very effective and in other ways it’s really annoying. But I guess that’s more
how real life is anyway” Sarah said, “Now I know how to depend on other people, and I
know how to provide to the team as well, or provide to just anybody who’s depending on
me.” Although they valued teamwork in the major, many of the SSI students interviewed
said they found the team work challenging (3/4 200 level and 2/4 400 level). They cited
113 different expectations and levels of engagement among team members as sources of
frustration.
BIO Group
Although they noted that biology classes tended to be lecture-driven, all BIO
participants said that they valued opportunities for independent research or participation
in a lab. They said those experiences helped them to see how science is really done.
Chloe noted that participation in a research lab helped her see how as a scientists, you use
“your own underlying process,” as opposed to a strict classroom definition of the
scientific method, where “they teach you rigid steps.” Ellen felt that her experience in a
research lab opened her eyes to new opportunities for discovery in biology she wouldn’t
have known from classes alone. She said, “Others may feel there’s one track to go
through biology—they’ve only seen one side of biology.” Polly also felt her experience
in her major was dramatically enhanced by participation in a research lab. When asked
how her experience would have been different if she had “just had the courses,” Polly
said, “Oh, I think it would be really different. Yeah, I wouldn’t know the material as well
probably. I wouldn’t enjoy it as much because I wouldn’t understand really as well as I
do, yeah, so that would be unfortunate I’d say.”
Other students felt that experiences in both research labs and course laboratories
reinforced their conceptual learning in their biology classes. Kevin said, “I know certain
people who do learn better from the books, but I believe more so people learn better from
the labs… You have to understand it if you do an experiment rather than just regurgitate
information you’ve heard about it.” Kevin also felt that the few inquiry-based course labs
he took helped him understand how scientists pose questions. He said, “…it actually
114 helped me to understand how to ask a good question, because there are so many questions
you have to mull over and it seems easy when you read about somebody else’s, but it’s
not nearly as easy as everybody makes it sound.”
Some BIO students also noted that research lab experience and course labs helped
them understand the breadth and big-picture goals of science. Natalie said, “I think that
the labs have helped me to have a glimpse of what kind of fields of biology are out there.
Like [histology class], I love it because I want to go into that field, pathology, or
histology.” Tracy noted, “It’s interesting [working in a lab] because you see what all this
work goes into. You see why you have to have the basic understanding.”
As well as laboratory experience, all BIO students said they valued opportunities
for discussion or debate. BIO participants described discussion sessions associated with
courses as opportunities to review concepts and work through problem sets in a nonthreatening environment with a graduate or advanced undergraduate student. Natalie said,
[I learn best in a] “discussion type thing, when the professors, they’re not down some
stairs all the way at the bottom of the lecture hall.” Carrie said, “I think [discussion
sessions are] definitely helpful, because you can see stuff hands on that’s just not being
like being lectured to you in class, like you can do that kind of stuff. I mean, discussion
helps a less threatening environment.” Polly noted, “I liked having to discuss something,
once again if you’re made to discuss something, it kind of furthers your understanding of
it.” Ellen mentioned that she also valued opportunities to discuss controversial issues in
her biology and social science courses. She said, “I welcome debates, but I think, I kinda
like when your perspectives are challenged because it allows you to prove what you
know, why you know it, and why it should matter.”
115 When discussing the level of community in their majors, all except one 400 level
BIO students said community isn’t facilitated, but develops, especially with
upperclassmen. They explained that the large size of the major makes developing a sense
of community difficult. Polly said, “I wouldn’t say it’s like collaborating is discouraged,
but it’s just not facilitated too much.” Kevin noted that the common practice of grading
on a curve in biology classes seemed to discourage some students from working with
other students. However, he said that many students worked together in spite of this. He
said, “Students studied together to help through difficult classes. It [grading on a curve]
should have discouraged us but in the end, being my friends in biology, it really incurred
us to work hard core together, get together, make schedules, because it would make us do
the work.” BIO participants also noted that a stronger sense of community developed in
upper-level students as class size decreased. Two discussed a particular social event for
senior biology majors that helped them feel more connected.
Although not all participants were specifically asked about interaction with
professors, the majority of them said that it was available when students sought it (2/4 at
400 level and all 200 level). When asked, “Do you have an opportunity to get to know the
professors?” Carrie said, “I would say that you have to make an effort to do that, it’s not
easy to do that. I especially think it’s hard when you’re doing well in the class, you don’t
really have any mood to go into office hours, so, you know.” Explaining that going to
office hours was the primary way to get to know their professors, BIO students said that
generally professors clearly wanted to help students.
116 CHAPTER 5: DISCUSSION
Review of Study
In summary, my dissertation looks for similarities and differences between
students in an SSI-based Human Biology major and students in a more traditional biology
major. I compare the two groups in terms of socioscientific reasoning, understanding of
scientific inquiry, and levels and perceptions of content knowledge. In addition I identify
themes in students’ general perceptions of their majors. The research questions divided
by topical sections of the study are as follows:
(1) Do Human Biology majors reason with SSI differently from traditional biology
majors?
(2) How do Human Biology and traditional biology majors’ perceptions of their
experiences with SSI differ?
(3) Do Human Biology and biology majors understand scientific inquiry differently?
(4) Do Human Biology and biology majors differ in their general biology content
knowledge?
(5) How do Human Biology and traditional biology majors’ perceptions of their content
knowledge differ?
(6) How do Human Biology and traditional biology majors’ general perceptions of their
majors differ?
117 I use a mixed methods convergence model of triangulation design (Creswell &
Plano Clark, 2007) comparing and contrasting various data sources including both
qualitative and quantitative data to develop interpretations (see Figure 1).
Note. Adapted from Creswell and Plano-Clark (2007).
In this chapter, I will discuss results from each section of the dissertation,
including socioscientific reasoning, understanding of inquiry, levels and perceptions of
content knowledge, and general major perceptions. I will then discuss limitations of the
study, major findings and their implications, and future directions for research.
Socioscientific Reasoning
The results of this study suggest that an SSI-focused interdisciplinary major in
Human Biology provides some benefits in reasoning and consideration of multiple
perspectives in complex problems over a traditional biology major. Although decisions
118 and the categories of factors considered in decision-making were similar for SSI and BIO
group, the SSI group showed higher levels of socioscientific reasoning. Consistent with
Bell’s and Lederman’s (2003) study with professors having different NOS views, few
differences were found in frequencies of decisions between the two groups. It is
unsurprising that positions differ little between similar groups of scientifically literate
pre-professionals. The only significant difference in decisions was based on whether
students exercised regularly. Although this question tested whether students based their
behavior on scientific knowledge, it did not ask them to take a position on a controversial
issue. SSI students were less likely to exercise regularly and they commonly reported
time constraints as the reason for this behavior.
Though few, some differences in reasons for decisions were found. BIO
participants were more likely to support legally binding limits on carbon emissions (more
pronounced at 200 level). One reason for this may relate to the fact that SSI participants
were more likely to suggest alternatives to legislation, like incentives (62% vs. 48%) in
this scenario. Perhaps having extensive experience with argumentation helped SSI
students to think creatively about alternatives to the suggested response. SSI participants
were also less likely to include environmental factors in their decisions (56% vs. 70%
BIO), so perhaps BIO students were more attuned to environmental concerns, whereas
SSI participants were more likely to focus on social concerns, or to more seriously
consider both socioeconomic and environmental aspects of the problem. Overall, for the
global warming cluster, SSI students included more reasons as influencing their decision,
so perhaps SSI students viewed the problem as more complex then the BIO groups.
Participants often noted that people would be affected differently by legislation, so
119 different approaches would be needed to assure fairness. In this cluster, SSI participants
were also more likely to refer to public perception of U.S. (24% vs. 10%). This difference
may relate to their focus on the social aspect of problems and consideration of different
perspectives. Many participants discussed how improving global perceptions of the U.S.
could facilitate cooperation in solving problems like global warming. Finally, SSI
participants were more likely to refer to evidence (44% vs. 34%) in their reasons for
making decisions in this cluster. This difference could relate to the explicit focus on
evidence-based arguments in their core courses.
400 level SSI participants were also more likely to answer “no,” (80% SSI vs.
50% BIO) when asked whether they thought cigarette smoking should be made illegal.
Like in the global warming cluster, this difference could be explained considering that
400 level SSI students were much more likely to cite availability of other options, like
banning smoking in public places, and the importance of personal responsibility as
reasons why smoking should not be banned (67% SSI vs. 35% BIO).
Finally, BIO majors were more likely to report that they make food and exercise
choices according to personal preferences or tastes (35% vs. 24%). This appears
consistent with SSI students’ lower participation in regular exercise. The reasons for this
difference are unclear. Although it seems SSI participants were aware of the benefits of
exercise and healthy diets, they were less likely to apply this knowledge to their own
lives.
Although most decisions and reasons behind decisions were similar, we expected
that reasoning processes would be more developed in SSI students. Theoretically, work in
socioscientific issues, which SSI students reported as having consistently and BIO
120 students as having infrequently, allowed students to develop reasoning processes that
could be applied to other issues. My analysis found that SSI students at both levels had
reasoning scores .25-.3 points higher on a 5-point scale. Both groups showed higher
reasoning scores for 400 level than 200 level, although the difference between classes for
the BIO group was slightly higher (.23 for BIO vs. .18 for SSI). Higher scores at the 400
level would be expected regardless of instruction, since higher levels of reflective
judgment, which relates to reasoning in SSI, would be expected with development and
experience in a college environment (King & Kitchener, 1994).
Still, I expected a greater difference between levels for SSI students as they have
consistently been exposed to socioscientific issues. Studies that compared SSI and nonSSI groups in pre-post improvement for more short-term interventions found greater
improvement in reasoning for SSI students (Tal & Hochberg, 2003; Zohar & Nemet,
2002; Dori et al., 2003). Also, Zeidler et al. (2009) found that students exposed to an SSI
curriculum for one school year improved in reflective judgment, while the non-SSI group
did not improve. Differences between 200 level and 400 level students cannot be
considered “improvement” as in pre-post studies, but with groups of students that were
originally very similar, these differences could be interpreted to show how extended
exposure to SSI (between the second and fourth year) affected gains over time in
reasoning with SSI. My findings may be partly explained by the small sample size of the
400 level classes and the newness of the Human Biology major. The 400 level SSI class
experienced the first implementation of the SSI curriculum in each year of their major.
When the 200 level group matriculated, program goals were more established, faculty
were more experienced, and the curriculum had been adapted. Also considering the
121 higher attrition rate in the BIO program, it is likely that for both majors the 200 level
groups were comparatively different from the 400 level groups.
Although pre-test data were not available, the consistent higher scores of the SSI
groups suggest that participation in the Human Biology program related to more
sophisticated socioscientific reasoning. SSI students were more likely to use multiple
justifications to support their positions and to better explain those justifications. This
likely relates to the focus on socioscientific reasoning in core courses. Students were
routinely challenged to make evidence-based arguments, using as much relevant and
credible data as possible. Their arguments were assessed in position papers and critiqued
by their peers and professors in debates.
It should be noted that average scores for both groups were fairly high (SSI: 3.46
and BIO: 3.19 on a 5-point scale). On average, students from both groups were likely to
include and elaborate on at least one justification of their positions. Few studies of
socioscientific reasoning have been conducted with college students, who should exhibit
much higher levels of intellectual development and reflective judgment than middle
school or high school students. Perhaps higher developmental levels, especially
considering the high achievement levels of my sample, may relate to the fairly small
difference in socioscientific reasoning. Also, perhaps a greater difference between groups
could have been found with a more sensitive instrument and coding scheme.
Consideration of Multiple Perspectives
For perspectives scores, no significant difference was found between groups
according to a Mann-Whitney test for non-parametric data. Still, it is worth noting that
although the number of DMQ items in which participant responses included multiple
122 perspectives was nearly equal between groups (BIO mean: 3.8; SSI: 3.9), of these
responses, SSI students scored a higher percentage of scores of 3 (55% vs. 47%), and
lower percentage of scores of 1 (34% vs. 43%). Although on average, BIO and SSI
students mentioned other perspectives an almost equal number of times in the
questionnaire, SSI students were more likely to consider other perspectives in depth and
reach a logical conclusion. Often in responses given a perspectives score of one, an
alternative perspective was referenced, but given no context. In responses scored 3 (more
frequent for SSI), alternate perspectives were considered in depth and the participant was
able to reach a resolution incorporating different perspectives. This result may be related
to the focus in Human Biology on fully considering different perspectives before
committing to a position. Incorporation of other perspectives was considered an
important part of a good argument, and students were assessed on how well this was
done. In the sophomore level core course, students were explicitly told, “The most
effective arguments will take into account the points made by the opposition.” Consistent
with this result, SSI students also consistently noted in interviews that they were more
likely to consider other perspectives than before entering the Human Biology major.
They reflected on the importance of being aware of other ideas and hearing from all
sides.
Few qualitative differences were seen considering the general principles of
reflective judgment between SSI and BIO interviewees in their responses to DMQ
follow-up questions. This may be explained by the fact that all students in this study were
high achieving pre-professionals who had reached high levels of development. However,
when probing reasoning processes on scenarios, SSI students tended to provide examples
123 from their core courses when they saw relevance. For example, two of the SSI students
interviewed compared a hypothetical argument that there is no clear causal mechanism
between smoking and cancer to the scientific debate over whether HIV causes AIDS
discussed in their core course. SSI students also mentioned many examples of cases from
their core courses when asked about their experiences with SSI or aspects of their major
that they valued. Perhaps extended experience with SSI, as provided in the Human
Biology major, provides a repertoire of cases students can access in relevant situations
(Bransford et al., 1986).
Views of Different Disciplines and Perspectives in Science
Consistent with in-class and interview assertions of Human Biology professors,
responses on the modified VOSI suggest that SSI students are more likely than BIO
students to view social science research as scientific inquiry. They more commonly
recognized that methods in social science, such as interviewing or using questionnaires
may not fit the scientific method, but are still scientific. In Human Biology core courses,
students read and discussed social science research articles, and professors stressed that
researchers from both social science and biological perspectives were scientists. In
interviews, some students mentioned inquiry projects they conducted in core courses,
which studied human behavior. These experiences as well as the discourse in Human
Biology classes likely contributed to this difference in understanding of inquiry.
Although they were more likely to mention social science research as part of
science, BIO students were somewhat more likely to indicate that scientists working
independently or collaboratively might reach different conclusions due to different
124 interpretations based on different backgrounds or perspectives of scientists. This is
surprising in light of interviews where SSI students were likely to discuss consideration
of multiple perspectives when thinking about scientific problems as a major program
outcome. Perhaps SSI students were more inclined to view “different perspectives” as
different disciplinary perspectives, rather than different ideas informing scientists
working in the same discipline on the same research. Although few students from each
group (8% BIO and 2% SSI) made the connection, BIO students were also slightly more
likely to cite new interpretations of existing data as a catalyst for theory change. This is
surprising considering that students discussed different interpretations of data in core
courses, such as the “Duesberg Phenomenon” with AIDS, and commonly referred to this
example in interviews. SSI students were more likely to report that theories are important
to promote discussion of the scientific community. Perhaps SSI students understood that
different interpretations led to debate and discussion, but did not connect them to theory
change.
It is important to note that the majority of both groups did not include subjectivity
in their reasoning for different conclusions between different scientists. SSI students were
more likely to cite error as a reason for differences in independent researchers’
conclusions (47% vs. 30%), and note that scientists do not use identical procedures (18%
vs. 4%). Both groups most commonly referred to different data resulting from
uncontrollable factors as contributing to differences in conclusions. An understanding
that people come from different perspectives, does not necessarily mean students will
recognize how different perspectives influence conclusions from specific data.
125 Views of the Scientific Method and Experiment
SSI majors were more likely than BIO majors to use the words, “scientific
method” when explaining how scientists investigate (36% vs. 20%). This is unsurprising,
considering that the term, “scientific method” was included in the discourse of core
courses. However, in core course discourse, the definition of scientific method was
broadly conceived to incorporate different aspects of scientific research, not presented as
rigid steps. The sociologist professor of the 200 level course said they were “with the first
year courses, pretty focused on a very traditional scientific method of approach and that
we’ve not abandoned the thinking, but they learn about other kinds of data that are used
to test hypothesis, generate hypothesis, and so on, in the second year of course.” Later in
the program, the scientific method was broadened to include other forms of science. The
sociologist professor said, “And then the contexts of, say reading about cholera, they
learn that Snow did things that weren’t experimental, and that he did observational work,
and followed sort of a scientific method in his approach to thinking thru the problem but
it wasn’t bench science, it isn’t what I think students necessarily come into college
thinking that science is.” The biologist professor of the 200 level course agreed,
In second year we really introduce the fact that you can’t apply those
methods strictly to everything. That there are other methods that you
utilize to make predictions and assess data…I think one of the things that
we try to do is emphasize that science is science. I mean, the word science
doesn’t apply to only bench scientists. People who do social science are
scientists. The scientific method can apply. You just have to use different
techniques, and you have to analyze the data differently, but it’s still
science. And it’s still valid.
Later in the interview, the 200 level professors continue their discussion of how they
present science and the scientific method:
126 Sociologist: There’s always as least one moment in each semester where
someone says something to me, well you know, Dr.[neuroscientist] is a
scientist, and you’re the sociologist, and I would say no, we’re both
scientists, we just do different kinds of science.
Neuroscientist – And I think that, I don’t think that we necessarily
explicitly set out to, on a mission, to fix that misconception but it is
something that, it’s a recurring issue and it’s something that we usually
spend the entire semester addressing over and over because when the kids
leave our classroom then they end up in the world where people make this
distinction again, and so we’re continually battling that and trying to help
them understand that science is this interdisciplinary concept and there are
a number of different ways that you address these scientific questions. Or
questions in general.
I mean science is just a way to address the
questions.
When asked, “Is there one scientific method or set of steps that all investigations
must follow to be considered science?” SSI and BIO groups were similar in their
responses (69% of SSI students and 72% of BIO students responded “yes”). However,
students who responded “yes” differed between groups, where SSI students were more
likely to include asking a question (49% vs. 22%) and making observations (27% vs.
8%). This is consistent with the fact that SSI students were more likely to report that
science begins with a question. The scientific method has promoted a common
misconception that inquiry begins with a hypothesis (Schwartz, Lederman, & Lederman,
2008). SSI students appear to grasp the idea that an inclusive scientific method
incorporates and begins with a problem or a question. Also, incorporation of observations
by SSI students suggests a broad conception of a scientific method, where knowledge
develops through other means than manipulating variables. BIO students were more
likely to include hypothesizing (68% vs. 23%) and analysis (40% vs. 29%) in their
responses, both traditional parts of the scientific method.
In their discussions of what scientists do, BIO participants were more likely to
discuss a purely experimental view of science (38% vs. 22%) and discuss specific process
127 skills of science, such as hypothesizing and collecting and analyzing data (80% vs. 69%).
Schwartz, Lederman, & Lederman (2008) assert that viewing inquiry as controlled
experiments is a common misconception among students. In their definitions of
“experiment,” BIO participants were more likely than SSI participants to include testing
of a hypothesis (74% vs. 60%) and ensuring validity or precision of experiments (18% vs.
7%). These differences may relate to the discourse in Human Biology core courses,
where science and the scientific method are inclusive of multiple forms of inquiry, but
maintain key processes in science, including “develop scientific questions, design and
conduct investigations, analyze and interpret data” (from a program revision document,
July 2009).
When asked to define “experiment,” most participants from both groups did not
explicitly distinguish an experiment from inquiry in general. Few students from both
groups (29% SSI and 24% BIO) mentioned that variables are isolated or controlled in an
experiment. These questionnaire results were consistent with student interviews. When
asked to give an example of an experiment, BIO participants were more likely to discuss
a study conducted in a research lab or by a research team (28% vs. 11%), although the
majority of students from both groups discussed personal experiences from class
activities. They were also slightly more likely to give an explanation why the example
they described was consistent with their definition of experiment (82% vs.76%). Perhaps
more exposure to experimental science (consistent with the finding that BIO students
were more likely to participate in research labs), not only affected BIO participants to see
inquiry as more experimental, but to develop coherence between examples of what
scientists do and their definitions of what scientists do.
128 Data and Evidence
Both groups saw data as different from evidence (89% SSI and 86% BIO), and
about half of each group said that evidence was different in that it is used to support an
argument (49% SSI and 54% BIO). More SSI students mentioned a similar idea, that
evidence is analyzed or interpreted data (9% vs. 2%). A greater percentage of interviewed
students had similar conceptions, but responses were also similar between groups. These
findings suggest that a majority of both groups grasp the primary difference between data
and evidence. On the questionnaire, BIO students were somewhat more likely to respond
that evidence is less precise or exact than data (12% vs. 4%), suggesting a common
misconception that data and evidence are hierarchical in their truth value.
SSI students more commonly reported two vague descriptions of data and
evidence. They much more commonly referred to data as “results” (22% vs. 8%), which
does not differentiate between raw data and analyzed data. They were also more likely to
report that data can be evidence, but not explain how they are different (11% vs. 2%).
Professors from the 200 level course agreed that their students struggled with presenting
evidence-based arguments, and felt more scaffolding was needed.
Neuroscientist: That’s been a real challenge for us is to help them
understand what evidence is. That’s something that we really struggled
with and work on this task this semester.
Sociologist: Yea. I think it will stick with some people and not with
others. We know we won’t get 100% but there might be people who need
us to give them explicit instruction about how you do that.
When asked, “What is ‘data analysis’?” and “What is involved in doing data
analysis?” both groups accurately responded interpretation or making meaning of data
(89% SSI and 96% BIO). However, SSI participants were much more likely to include
visualizing data through graphs or charts (29% vs. 14%) and checking validity or
129 accuracy of data collection (22% vs. 6%). They also included using statistics more (40%
vs. 30%) and compiling and reviewing data (16% vs. 6%). It is possible that SSI students
described more specific processes because of opportunities to carry out full inquiry
projects in their core courses. Most SSI students supported this in interviews, saying that
both Human Biology courses and an elective course in physiology helped them establish
an understanding of inquiry through experience. BIO participants may have differed more
in their experiences with inquiry. More BIO participants participated in research labs, but
interview participants discussed having had more “cookbook” laboratory experiences
than projects where they developed questions, collected and analyzed data, and drew their
own conclusions. Interviewees reported that an introductory level lab for BIO majors
included a culminating project where students independently conducted the full range of
inquiry with questions they had generated. Still, it is possible that SSI students were more
familiar with processes conducted at all stages of inquiry.
It is also interesting that 400 level students from both groups were much more
likely to include statistical tests (SSI increasing 50% and BIO increasing 42%) and
finding patterns in data (SSI increasing 17% and BIO increasing 20%). This finding
suggests that students become more familiar with specific methods in data analysis with
more experience.
Tentativeness of Theory and Purpose of Theory
The majority of both groups reported that theories are tentative (98% SSI and
96% BIO). Both groups commonly reported that discovery or availability of new data
contributed to theory change (49% SSI and 96% BIO), but BIO majors were more likely
to discuss new technology as a catalyst for change (16% vs. 7%). Perhaps BIO majors
130 were more attuned to advances in molecular and gene technology, which have recently
revolutionized research in biology. BIO students may have spent more time in class or
other settings with different biology professors, who may have been inclined to discuss
changes in research that result from new technology.
BIO majors were also more likely to discuss a falsification view of changing
theories, explaining that theories are put forth by scientists to be retested until they are
either disproven or withstand adequate attempts at falsification (26% vs. 8%). Chalmers
(1999) explains that this position is problematic in that theories are difficult to falsify
once and for all. Falsifying evidence may be found to be inaccurate or misinterpreted. In
addition, SSI students were more likely to report that theories are needed for lively
discussion within scientific communities (16% vs. 8%). Perhaps explicit discussion of
conflicting arguments and editorials in core courses such as the “Duesberg” debate
allowed them to recognize a lively discourse that changed thinking about scientific
controversies.
Both groups scored within one question of each other on the Biology Concept
Inventory, a finding that was consistent at both 200 and 400 levels. This suggests that
incorporating a focus on socioscientific issues did not detract from development of basic
content knowledge. Although differences were not seen in performance, in interviews,
SSI majors mostly felt confident in their basic content knowledge, but were less confident
in detailed content knowledge. Some mentioned that by participating in core courses and
courses from the social sciences and humanities, they were unable to take as many upper
level biology classes as they would if they had majored in biology. Some felt this was
131 reasonable, but others felt the major should have incorporated more biology content. BIO
majors interviewed were similarly confident in their basic biology knowledge, but felt
their knowledge of specific biology content depended on their interests and upper level
courses they had chosen.
It is unclear how Human Biology core courses contributed to students’ biology
content knowledge. The concepts included in the BCI were covered in introductory level
biology classes that both SSI and BIO majors were likely to have taken. Both groups
scored fairly low (a finding consistent with Klymkowsky, Furtak, Cooper, Garvan-Doxas,
& Gonzalas, submitted), indicating the persistence of many common misconceptions.
This was apparent in students’ answers to BCI validation questions in interviews.
Biology content addressed in Human Biology core courses depended on the topics
covered, and often covered specific topics in human anatomy and physiology, so major
misconceptions in evolutionary biology and genetics may not have been addressed. Some
SSI students recognized opportunities for deeper research into science concepts in core
courses, although not all students took advantage of these opportunities. Core courses
provided resources for deeper content learning and opportunities to research and reflect
upon biology concepts of interest.
Core course professors indicated that they considered application of biology
concepts a crucial part of the course. The neuroscientist professor said,
We shoot for a balance because we really do want to provide some content
and although content isn’t the goal of the Human Biology program or any
of the core courses, per say, we’re not trying to provide their content.
What we’re really looking to do is to integrate, or enhance their ability to
integrate what they are learning across their courses. But to do that and to
help the students understand that science is sort of a content based process
as well. We really use those exams to try to balance those things.
132 The professor gave the example of viruses as content knowledge that was presented in
class and incorporated into exams because it was a crucial part of understanding
problems related to disease. Although students may have learned new biology content
effectively and applied understandings gained in biology courses, they may not have had
additional opportunities, as compared to biology students, to improve the basic biology
content knowledge tested in the BCI.
Perceptions of Majors
When asked what they valued most about their experience in their majors, SSI
participants consistently cited having the opportunity to explore controversial
interdisciplinary issues in depth. They felt they had improved their abilities to discuss and
take positions on these issues, and they noted that this competency was essential for
future careers in science or health care. They also felt that the major offered them
opportunities to understand controversies they were not familiar with and situations they
never before saw as problematic. When asked what the major student outcomes
instructors worked toward, the neuroscientist instructor of the 200 level core course said,
“the major outcomes that we’re looking for mirror the outcomes of the program as a
whole, that we’re looking for the students to be able to think more critically, more
flexibly, about the problems that we talk about in the course, and what makes our course
specific is the context that we frame those problems within.” Clearly, SSI participants at
both levels grasped this central program goal.
BIO participants also valued many aspects of their major, although none of the
students voluntarily brought up reasoning with socioscientific issues as an important
133 outcome. They felt their major helped them learn to be more diligent and responsible,
which would serve them in future research and professional schools. Many discussed
rigors of the biology major, which sometimes discouraged them, but often made them
feel more prepared for future challenges. Most BIO students appreciated opportunities to
learn about new ideas and discover new passions for science.
Surprisingly, all students interviewed had taken classes that have explored
socioscientific issues to some degree. This may be partially due to a convenience sample
of highly motivated biology majors; all interview participants had experience working in
a research lab, compared to 27% BIO students sampled. Still, these experiences showed
that exploring socioscientific issues outside of Human Biology core courses is possible,
and many students pursue this interest. Although participants did not feel that their
biology courses offered opportunities to learn about or discuss socioscientific issues in
depth, many felt these courses helped them understand biological mechanisms more
thoroughly, which enhanced their understanding of socioscientific issues discussed in
other classes. One 200 level BIO participant explained that she was so disappointed in the
lack of opportunities to discuss SSI that she planned to change her major to anthropology
while maintaining a pre-medical curriculum. Tracy said,
You know when I started with a biology major, I was excited for what you
just said, to be able to apply my biological understanding in topics that
were relevant, that was on the news. And that’s the problem I fell into
was that the classes that I was taking, understandably, were the basics of
everything, that was my problem, it was like, when am I going to get to
the things that I can truly apply in my every day world? That’s not to say,
as I learn right now about the many steps of transcription and in
translation, it’s beautiful and I like to learn about it, but it would be cool to
watch the news and how they talk about global warming and the ice caps
melting and exactly be able to say, you know, why is that, why is it that
CO2 levels are contributing to the atmospheric thickening, where as I feel
134 like I almost get that information from the media, from watching An
Inconvenient Truth.
Kevin, while acknowledging the value of incorporating SSI into biology classes,
felt that avoiding controversy in biology courses was preferable. Clearly, biology courses
address a great deal of content, and some may argue that SSI should be explored through
other venues, like independent projects or other courses. The Human Biology core
courses may be considered a consistent venue for reasoning with SSI. The neuroscientist
professor of the 200 level core course explained that the Human Biology core courses
were designed specifically for this purpose, while biology courses should supply more indepth biology content. Addressing biology content, he said, “That’s what you’re going to
get if you want to learn cell biology, that’s why IU has a great resources, people who
know a lot about cell biology, you go over there and you take those courses, if it makes
sense for your curriculum.”
Still, professors in Human Biology recognized a resistance from students who felt
their core courses should supply more content. The 200 level neuroscientist professor
argued that content should be taught, but framed differently from a traditional biology
class. He said,
And you know, sort of the idea is that the content that we want them to
walk away with is content that will allow them to apply their newly gained
knowledge of bacteria to a variety of situations. Which I think is different
from the way they approach it in the biology department, and having sat
through some of those courses, I know that one of the things is you
memorize this, this is this specific bacteria and this is that specific virus
and you memorize what they look like. And we don’t so much care about
what they look like, we care about how is this disease similar to that one,
and why would you treat something with antibiotics and one infection
with antibiotics and another one you wouldn’t. Why is that? Those are the
kinds of questions that we want the students to be able to understand
because they see things on the news about this infection that’s occurring
and a lot of lay people say, oh take antibiotics. That doesn’t work!
135 This illuminates important questions for future research: “How should content and
socioscientific reasoning be balanced in college biology courses?” and “Should SSI be
provided in supplemental courses rather than integrating it into biology courses?” This
also raises the question whether socioscientific reasoning should be a mandatory or
optional part of undergraduate science training.
It is important to not that the learning environment played an important role in
students’ perceptions of their majors and personal outcomes. Both SSI and BIO groups
valued opportunities for discussion and application of concepts. BIO participants were
more likely to cite class discussion sessions and laboratories, and participation in research
labs as critical experiences for their learning. SSI participants more commonly cited case
studies as important opportunities to apply concepts. Throughout the interviews, SSI
participants cited many examples of case studies from core courses, and often related
them to other issues. This may have implications for transfer of knowledge and skills to
new problems.
Another important aspect of the learning environment involved a sense of
community. SSI participants valued a sense of family among students and professors.
Part of this they attributed to a small program, and part they attributed to the team-based
nature of core courses. They felt this aspect prepared them for collaborative work
environments and helped them develop confidence in their inter-personal skills and
public speaking skills. BIO participants did not feel that their major was structured to
support community, primarily because of its size. Interaction with professors was not
structured, but could be fruitful when students pursued that interaction. BIO participants
136 noted that the overall major and class size decreased in the junior and senior years, which
allowed for a desired sense of community to develop more easily.
This raises the question of how SSI learning environments need to be structured.
Sadler (2009) explains that participation in communities of practice (Lave, 1991) is
central to SSI. Students must come to understand the culture of the community, including
its rules and practices, and they adopt and project particular identities within those
communities. Can learning environments that purposefully nurture communities of
practice in SSI-contexts be structured for large classes, or is a small program size
important to this aspect? If effective communities of practice could be established
through an SSI framework in large majors like biology, could this help students feel more
supported and increase persistence in science majors?
Limitations of the Study
As a broad, exploratory study of a four-year program, this study had several
limitations. The conclusions are limited by unavailability of questionnaire pre data for
participants. Questionnaire differences between groups, though further explored and
supported through interviews, cannot necessarily be contributed to their experiences in
their majors. These differences may have been present initially in the samples.
Secondly, the two majors differ in diversity of students, since Human Biology is
more likely to attract students interested in the human divisions of the discipline.
Collection of demographic data helped to reveal similarities and differences of students in
the two majors. Possible curricula and focus areas are also more diverse for biology
students, so they are more likely to diverge in their coursework and experiences related to
biology.
137 A third limitation is the degree to which I may assume biology majors experience
“traditional” biology teaching. Interviews and anecdotal experience from occasional
visits to biology classes helped to ascertain that biology students primarily experience
lectures and “cookbook” labs, but I could not verify this through consistent observation
due to time constraints and the vast possibilities of classes to attend. BIO students
attested to my primary assumption that they did not experience yearly interdisciplinary,
SSI-based core courses. Still, most BIO students interviewed reported experiencing some
negotiation of socioscientific issues, and some took elective courses that specifically
addressed SSI. It is unclear how much these experiences contributed to BIO students’
reasoning with socioscientific issues.
Another limitation is that students who participated in interviews were not
representative of the total samples from each group. Interview participants were not
compensated for their time, so the majority of students originally selected were unable or
unwilling to participate. Clearly BIO participants included a disproportional number of
students with research lab experience, so it is unclear whether other factors may have
been disproportionately represented. Also, students willing to participate in interviews
may have been more inclined to promote their majors or speak to program goals. In
addition, I was more familiar to SSI students having been present in their core course,
and to some 400 level BIO students, having taught them in histology lab sections. This
may have influenced them to be more invested in my project. Interview participants were
treated as individual cases, but repetition of ideas from participants from each group was
considered convincing evidence for conclusions.
138 The instruments used also presented some limitations. For example,
misunderstandings in the implementation of the BCI resulted in loss of a significant
amount of data. Also, the DMQ questions resulted in fairly short responses that may not
have sufficiently captured students’ reasoning. Accordingly, the rubrics applied measured
very simple aspects of socioscientific reasoning, including number and explanation of
justifications and discussion of multiple perspectives. Longer and more in-depth
scenarios and questions may have produced data appropriate to a more sensitive rubric
for socioscientific isues.
Considering the research-based foundations of practices in Human Biology and
consistency of observed teaching and classroom activities with these principles, larger
differences favoring the SSI group were expected in socioscientific reasoning and views
of scientific inquiry. Since the program was only in its fourth year, teaching strategies
may have varied among core courses and from year to year, and aspects of program goals
were likely implemented inconsistently.
Finally, my presence in Human Biology classes as a researcher and position as an
instructor in the histology labs may have limited my findings. Students in Human
Biology became familiar with me through my frequent class observations and
participation in Human Biology events. They knew I had worked with the program
director and was supportive of the program. These students may have been more willing
to participate in the study, since it could potentially lead to advancement and
improvement of the program. Also, having interacted frequently with the students while
in the classroom, they may have wanted to help me with my dissertations. Similarly,
biology students from my 400 level histology course may have been more willing to
139 participate, having known me as an instructor. Students who knew me before the study
may have invested more thought and effort in the questionnaires which may have
affected the results.
Major Findings and Implications
Major findings in response to research question 1, “Do Human Biology majors
reason with SSI differently from traditional biology majors?” are that SSI students
showed enhanced socioscientific reasoning according to a simple scale, and that they
appear to be more likely to incorporate different perspectives into their decision making.
Perhaps more in-depth instruments, similar to position papers and debates held in core
courses would reveal greater differences. In response to research question 2, “How do
Human Biology and traditional biology majors’ perceptions of their experiences with SSI
differ?” interviews showed that SSI students “bought in” to the goal of recognizing
different perspectives in decision making and increased in their perceptions of
controversy or problematic situations. In addition, SSI students appeared to use case
studies from core courses to reason with new similar problems. These findings together
suggest that classroom experience with socioscientific reasoning through case studies,
with a focus on integrating different perspectives, impacts students in their awareness of
and approach to real-life problems as well as their ability to reason effectively with such
problems.
In response to research question 3, “Do Human Biology and biology majors
understand scientific inquiry differently?” SSI and BIO majors do show some
140 differences. SSI students are somewhat more likely to include social science inquiry in
their definition of scientific inquiry, presumably because they have been exposed to
scientists and research from different disciplines. They were able to discuss specific
processes of scientific inquiry, attributing their understanding to Human Biology core or
elective classes. However, SSI students, like the BIO students, still appeared to be
confused about the nature of evidence, although they were slightly more likely to refer to
using evidence in their decision making on the DMQ global warming scenario. Human
Biology professors expressed that their students had difficulty understanding the concept
of backing up arguments with evidence, although they explicitly addressed it in class.
Perhaps more scaffolding in evidence-based reasoning with explicit discussion of the
meaning of evidence is needed. Also, this confusion raises the question of how students
conceive of evidence to back up scientific claims versus evidence to back up decisions on
socioscientific issues. These different applications nuance the meaning of evidence and
may contribute to confusion.
In response to research question 4, “Do Human Biology and biology majors differ
in their general biology content knowledge?” findings from a very limited sample suggest
that SSI and BIO majors do not differ in their basic biology content knowledge. In
response to question 5, “How do Human Biology and traditional biology majors’
perceptions of their content knowledge differ?” Human Biology students may feel that
they are receiving a less rigorous biology content learning experience as compared to
biology majors. Professors have attempted to clarify that core courses are not centered in
content, but socioscientific reasoning. This raises the question, “Where is the most
141 effective place in a college environment to teach SSI?” Are optional interdisciplinary
courses like Human Biology core courses that attract a small population of students
preferable to required science courses integrated with SSI?
In response to Question 6, “How do Human Biology and traditional biology
majors’ general perceptions of their majors differ?” interviews suggested that all students
valued their majors and were satisfied with personal outcomes. SSI students consistently
viewed integrating different perspectives and social aspects of scientific problems as
significant program outcomes. SSI students also valued aspects of the learning
environment designed to support ethical, cognitive, and epistemological development,
including an inclusive, collaborative environment and supportive relationships with
faculty. SSI students felt a greater sense of community as compared to BIO students.
These findings support the idea that careful structuring of the learning environment
provides essential components of learning through SSI.
Future Directions
This exploratory work leads to new research on outcomes of SSI learning
environments for college science majors, for which little research has been published.
One future direction is to investigate how SSI learning environments affect students’
thinking about science careers. For example, I would like to investigate whether SSI
students are more likely to perceive complexity of problems faced by science
professionals and if they recognize a need to incorporate different perspectives. For
example, how might exposure to SSI influence a premedical student to think about
addressing different aspects of patients that influence their health, such as availability of
142 healthy food, limitations on their ability to travel to clinics or pharmacies, or
psychological states that may influence behavior? This study would incorporate
background study and interviews with science professionals to better understand the
situations in which interdisciplinary collaboration and understanding of different
perspectives are needed. Pre and post tests including scenarios faced by science
professionals as well as interviews would assess changes in students’ thinking about these
issues.
Another direction for future research is a more in-depth look at how students’
understanding of inquiry is facilitated in an SSI-based course. This would involve a case
study of an SSI-based course to reveal opportunities afforded by the curriculum to
discuss and experience scientific inquiry. I would further document how an SSI-based
environment may help students develop understandings of inquiry that include fields
outside the boundaries of what is traditionally considered “science.” I would also further
consider how students come to understand evidence in scientific inquiry. For example, do
they see similarities between using evidence to support their positions on issues and
scientists supporting their conclusions with evidence from their investigations? Do
students understand the relationship between data and evidence? Such a study would
involve careful consideration of the curriculum and intended methods of teaching inquiry,
continual debriefing with the teacher, and observation as well as pre and post instruments
and interviews to gauge student thinking about inquiry.
Conclusion
Overall, this study contributes to our understanding of how an SSI-focused, fouryear program can help students reason and make informed decisions on real and complex
143 problems. With the assumption supported that traditional university biology teaching
provides few opportunities for critical evaluation of interdisciplinary problems currently
called for (AACU, 2007), it provides an example of effective SSI teaching, with
modeling of reasoning from social science and biological disciplinary perspectives. The
study provides a springboard for new studies investigating SSI in interdisciplinary
college contexts.
144 REFERENCES
Adams, L. T., Perfetto, G. A., Yearwood, A., Kasserman, J., Bransford, J. D., & Franks,
J. J. (1985). Facilitating Access. Unpublished manuscript, Vanderbilt University.
Albanese, M.A. and Mitchell, S. (1993). Problem-based learning: a review of literature
on its outcomes and implementation issues. Academic Medicine, 68, 52-81.
Albe, V. (2008). When scientific knowledge, daily life experience, epistemological and
social considerations intersect: Students’ argumentation in group discussion on a
socio-scientific issue. Research in Science Education, 38, 67–90.
American Association for the Advancement of Science. (1990). Science for all
Americans. New York: Oxford University Press.
Association of American Colleges and Universities. (2007). College Learning for the
New Global Century. Washington, D.C.: AACU.
Barber, M. (2001). A comparison of NEAB and Salters A-level Chemistry: Students
views and achievements. York, UK: University of York.
Barker, V., & Millar, R. (1996). Differences between Salters’ and traditional A-level
chemistry students’ understanding of basic chemical ideas. York, UK: University
of York.
Barron, B., Schwartz, D., Vye, N., Moore, A., Petrosino, A., Zech, L., Bransford, J. &
Cognition and Technology Group at Vanderbilt. (1998). Doing with
understanding: Lessons from research on problem- and project-based learning.
Journal of the Learning Sciences, 7, 271-312.
Baxter Magolda, M. (1992) Knowing and reasoning in college: Gender-related patterns
in students’ intellectual development. San Francisco: Jossey-Bass.
Baxter Magolda, M. (1999). Creating Contexts for Learning and Self-Authorship
Constructive-Developmental Pedagogy. Nashville, TN: Vanderbilt University
Press.
Bell, R. & Lederman, N. 2003. Understandings of the nature of science and decision
making on science and technology based issues. Science Education, 87, 352–
377.
Bell, P., & Linn, M. C. (2000). Scientific arguments as learning artifacts: Designing for
learning from the web with KIE. International Journal of Science Education,
22(8), 797-817.
Blattner, W., Gallo, R.C., & Temin, H.N. (1988). HIV casuses AIDS. Science, 241, 515516.
145 Boix Mansilla, V. & Duraising, E. (2007). Targeted assessment of students’
interdisciplinary work: An empirically grounded framework. The Journal of
Higher Education,78, 215-237.
Boix Mansilla, V., Miller, W.C., Gardner, H. (2000). On disciplinary lenses and
disciplinary work. In S. Wineburg & P. Grossman (Eds.), Interdisciplinary
curriculum: Challenges to implementation. (pp. 1-16). New York, NY: Teachers
College Press.
Bossert, S.T. (1988). Cooperative activities in the classroom. Review of Research in
Education, 15, 225-250.
Bransford, J., Sherwood, R., Vye, N., & Reiser, J. (1986). Teaching thinking and
problem solving: Suggestions from research. American Psychologist, 41, 10781089.
Brown, A. & Palincsar, A. (1989). Guided, cooperative learning and individual
knowledge acquisition. In L. Resnick (Ed.), Knowledge, Learning and Instruction
(pp. 307-336). Hillsdale, NJ: Lawrence Erlbaum Associates.
Brown, J.S., Allan Collins, A., & Duguid, P. (1989). Situated cognition and the culture
of learning, Educational Researcher, 18, 32 - 42.
Chalmers, A.F. (1999). What is this thing called science? Australia: University of
Queensland Press.
Cognition and Technology Group at Vanderbilt (CTGV). (1990). Anchored instruction
and its relationship to situated cognition. Educational Researcher, 19, 2-10.
Colliver, J.A. (2000). Effectiveness of problem-based learning curricula: research and
theory. Academic Medicine, 75, 259-66.
Commission on Behavioral and Social Sciences and Education (CBASSE). (1999). How
People Learn: Brain, Mind, Experience, and School. Washington D.C.: National
Academy Press.
Committee on Behavioral and Social Sciences in Medical School Curriculum, Institute
of Medicine of the National Academies. (2004). Improving medical education:
Enhancing the behavioral and social science content of medical school curricula.
Washington, D.C.: National Academies Press.
Cohen, E. (1994). Restructuring the classroom: Conditions for productive small groups.
Review of Educational Research, 64, 1-35.
Creswell, J. (2009). Research Design: Qualitative, Quantitative, and Mixed Methods
Approaches. Los Angeles, CA: SAGE Publications.
D’Avanzo, C. (2008). Biology Concept Inventories: Overview, Status, and Next Steps.
BioScience, 58, 1079-1085.
146 Davidson, N. (1985). Small group learning and teaching in mathematics: A selective
review of the research. In R. Slavin, S. Sharan, S. Kagan, R. Hertz-Lazarowitz, G.
Webb, & R. Schmuck (Eds.), Learning to cooperate, cooperating to learn. New
York: Plenum.
Dochy, F., Segers, M., Van den Bossche, P., & Gijbels, D. (2003). Effects of problembased learning: A meta-analysis. Learn. Instr. 13: 533–568.
Dori, Y.J., Tal, R., & Tsaushu, M. (2003). Teaching biotechnology through case studies:
Can we improve higher-order thinking skills of non-science majors? Science
Education, 87, 767–793.
Duesberg, P. (1988). HIV is not the cause of AIDS. Science, 241, 514-517.
Fink, L. (2002). Beyond small groups: Harnessing the extraordinary power of learning
teams. In L. K. Michaelsen, A. B. Knight, and L. D. Fink (Eds.), Team-Based
Learning: a Transformative Use of Small Groups (pp.3-26). Westport, CT:
Praeger Press.
Fleming, R. (1986a). Adolescent reasoning in socio-scientific issues. Part I: Social
cognition. Journal of Research in Science Teaching, 23, 677–687.
Gijlers, H. & de Jong, T. (2005). The relation between prior knowledge and students’
collaborative discovery learning processes. Journal of Research in Science
Teaching, 42,264-282.
Gore, A. (2006). An Inconvenient truth The planetary emergency of global warming and
what we can do about it. New York, NY: Rodale.
Grossman, P., Wineburg, S., Beers, S. (2000). Introduction: When theory meets practice
in the world of school. In S. Wineburg & P. Grossman (Eds.), Interdisciplinary
curriculum: Challenges to implementation. (pp. 1-16). New York, NY: Teachers
College Press.
Harris, R., & Ratcliffe, M. (2005). Socio-scientific issues and the quality of exploratory
talk--what can be learned from schools involved in a ‘collapsed day’ project?
Curriculum Journal, 16, 439–453.
Hmelo-Silver, C., Duncan, R., & Chinn, C. (2007). Scaffolding and achievement in
problem-based inquiry learning: a response to Kirschner, Sweller, and Clark.
(2006). Educational Psychologist, 42, 99-107.
Hmelo, C.E., & Evensen, D.H. (2000). Problem-based learning: Gaining insights on
learning interactions through multiple methods of inquiry. In C. E. Hmelo, & D.
H. Evensen (Eds.), Problem-based learning: A research perspective on learning
interactions (pp. 1-19). Mahwah, NJ: Lawrence Erlbaum.
Hogan, K. (1999). Thinking aloud together: A test of an intervention to foster students’
collaborative scientific reasoning. Journal of Research in Science Teaching, 36,
1085-1109.
147 Hogan, K. (2002). Small groups’ ecological reasoning while making an environmental
management decision. Journal of Research in Science Teaching, 39, 341–368.
Hogan, K., Nastasi, B.K., & Pressley, M. (2000). Discourse patterns and collaborative
scientific reasoning in peer and teacher-guided discussions. Cognition und
Instructional, I7 (4), 379-432.
Human Biology Program, Indiana University (2007). Welcome to Human Biology at
Indiana University. Retrieved December October 1, 2008, from
http://www.indiana.edu/~humbio.
Kavalovsky,V. C. (1979). Interdisciplinary education and humanistic aspiration. In J. J.
Kockelmans (Ed.), Interdisciplinarity and higher education(pp. 224–43).
University Park, PA:Pennsylvania State University Press.
Khishfe, R., & Lederman, N.G. (2006). Teaching nature of science within a controversial
topic: Integrated versus non-integrated. Journal of Research in Science Teaching,
43, 395–318.
King, P. M., & Kitchener, K. S. (Eds.). (1994). Developing reflective judgment:
Understanding and promoting intellectual growth and critical thinking in
adolescents and adults. San Francisco: Jossey-Boss.
Kinneavy, J. (1980). A theory of discourse. New York, NY: Norton.
Klahr, D., & Dunbar, K. (1988). Dual space search during scientific reasoning. Cognitive
Science, 12, 1-55.
Klymkowsky, M. W. & Garvin-Doxas, K. (2008). Recognizing student misconceptions
through Ed’s Tools and the Biology Concept Inventory. PLoS Biology, 6, 14-17.
Kolodner, J., Hmelo, C., Narayanan, N. (1996). Problem-based learning meets case-based
reasoning. Proceedings of the 1996 international conference on Learning
sciences, 188-195.
Kuhn, D. (1993). Science as argument: Implications for teaching and learning scientific
thinking. Science Education, 77, 319–337.
Land, S. & Zembal-Saul, C. (2003). Scaffolding reflection and articulation of scientific
explanations in a data-rich, project-based learning environment: An investigation
of progress portfolio. Educational Technology Research and Development, 51,
65-84.
Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation.
Cambridge: Cambridge University Press.
Lederman, N. (2003). Introduction. In D.L. Zeidler (Ed.),The Role of Moral Reasoning on
Socioscientific Issues and Discourse in Science Education (pp. 1-4). Norwell,
MA: Kluwer Academic Publishers.
148 Lederman, N.G., Abd-El-Khalick, F., Bell, R.L., & Schwartz, R.S. (2002). Views of
nature of science questionnaire: Toward valid and meaningful assessment of
learners’ conceptions of nature of science. Journal of Research in Science
Teaching, 39, 497–521.
Michaelson, L., Watson, W., Black, R. (1989). A realistic test of individual versus group
consensus decision making. Journal of Applied Psychology, 74, 834-839.
Morse, J.M. (1991). Approaches to qualitative-quantitative methodological triangulation.
Nursing Research, 40, 120-123.
National Research Council. (1996). National science education standards. Washington,
DC: National Academy Press.
Newell,W., & Green,W. J. (1982/1998). Defining and teaching interdisciplinary studies.
In W. Newell (Ed.) Interdisciplinarity: Essays from the literature. (pp. 23–30).
New York: College Board Publications.
Norman, G. & Schmidt, H. (1992). The psychological basis of problem-based learning: a
review of the evidence. Academic Medicine. 67, 557-65.
Okada, T. & Simon, H. A. (1997). Collaborative discovery in a scientific domain.
Cognitive Science, 21, 109-146.
Pedretti, E. (1999). Decision making and STS education: Exploring scientific knowledge
and social responsibility in schools and science centers through an issues-based
approach. School Science and Mathematics, 99, 174–181.
Perkins, D.N., Farady, M., & Bushey, B. (1991). Everyday reasoning and the roots of
intelligence. In J.F. Voss, D.N. Perkins, & J.W. Segal (Eds.), Informal reasoning
and education (pp. 83–105). Hillsdale, NJ: Erlbaum.
Perry, W. G. (1979). Forms of intellectual and ethical development in the college years:
A scheme. New York, NY: Holt, Rinehart and Winston.
Roberts, D.A. (2007). Scientific literacy / science literacy. In S.K. Abell, & N.G.
Lederman (Eds.), Handbook of research on science education (pp. 729 – 780).
Mahwah, NJ: Lawrence Erlbaum Associates.
Roschelle, J. (1992). Learning by collaborating: Convergent conceptual change. Journal
of the Learning Sciences, 2, 235-276.
Rutherford, F. and Ahlgren, A. (1991). Science for All Americans. Retrieved October 30,
2008, from http://www.project2061.org/publications/sfaa/online/intro.htm.
Sadler, T.D. (2004). Informal reasoning regarding socio-scientific issues: A critical
review of research. Journal of Research in Science Teaching, 41, 513–536.
Sadler, T. D. (2009). Situated learning in science education: socio-scientific issues as
contexts for practice, Studies in Science Education, 45, 1-42.
149 Sadler, T., Barab, S., Scott, B. (2007). What do students gain by engaging in
socioscientific inquiry? Research in Science Education, 37, 371-391.
Sadler, T. D. & Zeidler, D. L. (2009). Scientific literacy, PISA, and socioscientific
discourse: Assessment for progressive aims of science education. Journal of
Research in Science Teaching, 46, 909-921.
Savery, J. R., and Duffy, T. M. (1995). Problem based learning: An instructional model
and its constructivist framework. Educational Technology, 35, 31-38.
Schilling, K. L. (2001). Interdisciplinary assessment for interdisciplinary programs. In B.
L. Smith & J. McCann (Eds.), Reinventing ourselves: Interdisciplinary
education, collaborative learning and experimentation in higher education (pp.
344–54). Bolton, MA: Anker.
Schlegel, W. M. & Pace, D. (2004). Using collaborative learning to decode the
disciplines in physiology and history. In: J. Mittendorf & D. Pace (Eds.),
Decoding the disciplines: How do we more effectively bring students into the
thinking we do in our disciplines? Editors: Joan Mittendorf and David Pace. San
Francisco, CA: Jossey-Bass Publishers.
Schwartz, Lederman N.G., & Lederman R.S. (2008, March). An Instrument to assess the
views of scientific inquiry: the VOSI questionnaire. Paper presented at the annual
meeting of the National Association for Research in Science Teaching, St. Louis,
MO.
Schwartz, R. S., Lederman, N. G., & Thompson, R. (2001, March). Grade nine students’
views of nature of science and scientific inquiry: The effects of an inquiry
enthusiast’s approach to teaching science as inquiry. Paper presented at the
annual meeting of the National Association for Research in Science Teaching,
Baltimore, MD.
Sherwood, R., Petrosino, A., Lin, X.D., and the Cognition and Technology Group at
Vanderbilt. (1998). Problem based macro contexts in science instruction: Design
issues and applications. In B.J. Fraser & K. Tobin (Eds.), International handbook
of science education (pp. 349-362). Dordrecht, Netherlands: Kluwer.
Springer, L., Stanne, M., Donovan, S. (1999). Effects of small-group learning on
undergraduates in science, mathematics, engineering, and technology: A meta
analysis. Review of Educational Research, 69, 21-51.
Tal, R., & Hochberg, N. (2003). Assessing high order thinking of students participating
in the ‘WISE’ project in Israel. Studies in Educational Evaluation, 29, 69–89.
Tal, T., & Kedmi, Y. (2006). Teaching socio-scientific issues: Classroom culture and
students’ performances. Cultural Studies in Science, 1, 615–644.
Thompson Klein, J. (1990). Interdisciplinarity: History, Theory, and Practice. Detroit,
MI: Wayne State University Press.
150 Tytler, R., Duggan, S., & Gott, R. (2001). Dimensions of evidence, the public
understanding of science and science education. International Journal of Science
Education, 23, 815–832.
Vernon, D.T. & Blake, R.L. (1993). Does problem-based learning work? A meta-analysis
of evaluative research. Academic Medicine, 68, 550-63.
Walker, K.A., & Zeidler, D.L. (2007). Promoting discourse about socio-scientific
issues through scaffolded inquiry. International Journal of Science Education,
29,1387–1410.
Willaims, S. (1992). Putting case-based instruction into context: examples from legal and
medical education. Journal of the Learning Sciences, 2, 367-427.
Yager, S.O., Lim, G., & Yager, R. (2006). The advantages of an STS approach over a
typical textbook dominated approach in middle school science. School Science
and Mathematics, 106, 248–260.
Zeidler, D. (2001). Participating in program development: Standard F. In D. Siebert & W.
McIntosh (Eds.), College pathways to the science education standards (p. 18-22).
Arlington, VA: National ScienceTeachers Press.
Zeidler, D. & Keefer, M. (2006). The role of moral reasoning and the status of
socioscientific issues in science education: Philosophical, psychological, and
pedagogical considerations. In D.L. Zeidler (Ed.),The Role of Moral Reasoning on
Socioscientific Issues and Discourse in Science Education (pp. 7-38). Norwell,
MA:Kluwer Academic Publishers.
Zeidler, D., Sadler, T., Applebaum, S., Callahan, B. (2009). Advancing reflective
judgment through socioscientific issues. Journal of Research in Science
Teaching, 46, 74-101.
Zeidler, D.L., Sadler, T.D., Simmons, M.L., & Howe, E.V. (2005). Beyond STS: A
research-based framework for socioscientific issues education. Science
Education, 89.
Zeidler, D.L. & Schafer, L.E. (1984). Identifying mediating factors of moral reasoning in
science education. Journal of Research in Science Teaching, 21, 1-15.
Zohar, A. & Nemet, F. (2002). Fostering students’ knowledge and argumentation skills
through dilemmas in human genetics. Journal of Research in Science Teaching,
39, 35-62.
151 Appendix A
Informed Consent Statement
IRB Study #09-13719
INDIANA UNIVERSITY BLOOMINGTON
INFORMED CONSENT STATEMENT
Student Development in Biology (Student)
You are invited to participate in a research study of student development of conceptual and disciplinary knowledge in
four-year biology programs. You were selected as a possible subject because you are a participant in Human Biology or
Biology degree programs. We ask that you read this form and ask any questions you may have before agreeing to be in the
study.
The study is being conducted by Jennifer Eastwood, Science Education, Indiana University, Bloomington. This is an
unfunded dissertation study.
STUDY PURPOSE
The purpose of this study is to understand students’ perceptions of their experiences in their degree programs, and their
understandings of biology content, scientific inquiry, and social issues related to biology.
NUMBER OF PEOPLE TAKING PART IN THE STUDY:
If you agree to participate, you will be one of 168 subjects who will be participating in this research.
PROCEDURES FOR THE STUDY:
If you agree to be in the study, you will do the following things:
•
•
•
Complete one survey, which will take between 1 1/2 and 2 hours to complete. The survey includes a section on
biology content knowledge, understanding of scientific inquiry, and reasoning on social and scientific issues. Its
purpose is to test content knowledge and collect student views on inquiry and social/scientific issues.
Allow the researcher access to assignments you have completed in Human Biology coursework, which have been
submitted electronically to Oncourse or your e-portfolio.
You may be asked to participate in one or two audiotaped interviews, ranging between 30-45 minutes. Please
check a box below and place your initials next to the box stating whether or not you would be willing to
participate in the interview portion:
______
(intials)
Yes, please contact me about participating in audiotaped interviews. I understand that if I
do not want to participate later that I may chose not to.
______
(initials)
No, please do not contact me about participating in audiotaped interviews.
RISKS OF TAKING PART IN THE STUDY:
While on the study, the risks or discomforts are: feeling uncomfortable in an interview or answering questions on the
surveys, and a small risk of losing confidentiality. Great care will be taken to ensure that confidentiality is protected, and
any data connected to your name and/or voice will only be seen by the researcher. No names or identities will be reported
in publications or presentations of this research.
BENEFITS OF TAKING PART IN THE STUDY:
The benefits to participation that are reasonable to expect are having the opportunity to assess your own learning through
surveys, and reflecting on your experiences in interviews.
ALTERNATIVES TO TAKING PART IN THE STUDY:
152 Instead of being in the study, you have these options: You may choose not to participate in surveys or interviews. All
student work collected will be normal classroom assignments, so you may choose not to allow the researcher access to
your work.
CONFIDENTIALITY
Efforts will be made to keep your personal information confidential. We cannot guarantee absolute confidentiality. Your
personal information may be disclosed if required by law. Your identity will be held in confidence in reports in which the
study may be published. All voice recordings will be destroyed within 10 years.
Organizations that may inspect and/or copy your research records for quality assurance and data analysis include groups
such as the study investigator and his/her research associates, the IUB Institutional Review Board or its designees, the
study sponsor, and (as allowed by law) state or federal agencies, specifically the Office for Human Research Protections
(OHRP) etc., who may need to access your research records.
PAYMENT
You will receive compensation of $20 for taking part in this study.
CONTACTS FOR QUESTIONS OR PROBLEMS
For questions about the study or a research-related injury, contact the researcher, Jennifer Eastwood at
jvanduse@indiana.edu.
For questions about your rights as a research participant or to discuss problems, complaints or concerns about a research
study, or to obtain information, or offer input, contact the IUB Human Subjects office, 530 E Kirkwood Ave, Carmichael
Center, L03, Bloomington IN 47408, 812-855-3067 or by email at iub_hsc@indiana.edu
VOLUNTARY NATURE OF STUDY
Taking part in this study is voluntary. You may choose not to take part or may leave the study at any time. Leaving the
study will not result in any penalty or loss of benefits to which you are entitled. Your decision whether or not to
participate in this study will not affect your current or future relations with the investigator(s).
SUBJECT’S CONSENT
In consideration of all of the above, I give my consent to participate in this research study.
I will be given a copy of this informed consent document to keep for my records. I agree to take part in this study.
Subject’s Printed Name:
Date:
Subject’s Signature:
(must be dated by the subject)
Printed Name of Person Obtaining Consent:
Date:
Signature of Person Obtaining Consent:
V. 12/2008
1
153 Appendix B
Overhead Slide for Participant Recruitment
!"##$%&'()*+,&-./+)0+,&-.$*&+1$'%*"*2+"*+3*.$%2%'.-'&$+4")5)2/+
•!6+'7+"*&$%$#&$.+"*+8)9+&8$+5$'%*"*2+$*:"%)*7$*&+'*.+;%)2%'7+#&%-<&-%$+'=$<&+
#&-.$*&+5$'%*"*2+'*.+;$%<$;()*#+)0+>")5)2/+<)*&$*&?+-*.$%#&'*."*2+)0+"*@-"%/?+
'*.+%$'#)*"*2+9"&8+#)<"'5+'*.+#<"$*(A<+"##-$#B+
•!C)-%+;'%(<";'()*+"*<5-.$#D+
•!E+#-%:$/+0)<-#"*2+)*+>")5)2/+<)*&$*&?+#<"$*(A<+"*@-"%/?+'*.+
#)<")#<"$*(A<+"##-$#+
•!E>)-&+F+G+8)-%#+
•!H'I$*+"*+4'55'*(*$+<)7;-&$%+5'>#+
•!JKL+<)7;$*#'()*++
•!H"7$#+':'"5'>5$D++
M)*?+M'%<8+KND+O;7+)%+PDNL+;7+
Q$.?+M'%<8+KO?+ODNL+;7+
H8-%?+M'%<8+KP?+PDFO+;7+
R%"?+M'%<8+KS?+KDNL+;7+
•!E+0$9+#&-.$*&#+9"55+>$+'#I$.+&)+;'%(<";'&$+"*+'+#8)%&+"*&$%:"$9+
R$$5+0%$$+&)+<)*&'<&+7$?+T$**"0$%+U'#&9)).?+V:'*.-#$W"*."'*'B$.-+
154 Appendix C
Demographic Sheet
Name:__________________________
ID Number (entered on survey)_______________
1. What is your major?
2. What is your minor?
3. What is your gender?
4. What is your race/ethnicity?
5. Do you have a focus area? (pre-medical, ecology, molecular biology, etc.)?
6. How many college-level biology classes have you taken (including this semester)?
Science classes?
Social science classes?
7. What do you plan to do after graduation (graduate school, medical school, etc.)?
8. What is your GPA?
Major GPA?
9. Why did you choose your major?
155 10. What extra-curricular (outside of course requirements) activities are you involved in? For
each, how long have you been involved?
11. Have you worked in a research lab? _________
If yes, how long were you involved?
What is the focus of that lab?
What is/was your reason for being involved in the lab?
12 Have you been involved in teaching in your undergraduate career?
If so, which classes?
Describe your role.
156 Appendix D
Open-ended Questionnaire
ID number___________________
Questionnaire: Scientific Inquiry, Biology Content, and Social and Scientific Issues
PART I: VIEWS ON SCIENTIFIC INQUIRY
Adapted from Schwartz et al. (2008)
The following questions are asking for your views related to science and scientific
investigations. There are no right or wrong answers.
Please answer each of the following questions. You can use all the space provided to
answer a question and continue on the back of the pages if necessary.
1. What types of activities do scientists do to learn about the natural world? Be specific
about how they go about their work.
2. What scientists choose to study and how they learn about the natural world may be
influenced by a variety of factors. How do scientists decide what and how to
investigate? Describe all the factors you think influence the work of scientists. Be as
specific as possible.
3. (a) Write a definition of a scientific experiment?
A scientific experiment is……
(b) Give an example from something you have done or heard about in science that
illustrates your definition of a scientific experiment.
(c) Explain why you consider your example to be a scientific experiment.
4. Some people have claimed that all scientific investigations must follow the same
general set of steps or method to be considered science. Others have claimed there are
different general methods that scientific investigations can follow.
157 (a) What do you think? Is there one scientific method or set of steps that all
investigations must follow to be considered science? Highlight one answer:
•
Yes, there is one scientific method (set of steps) to science.
• No, there is more than one scientific method to science.
•
If you answered “yes,” go to (b) below.
If you answered “no,” go to (c) below.
(b) If you think there is one scientific method, what are the steps of this method?
(c) If you think that scientific investigations can follow more than one method,
describe two investigations that follow different methods. Explain how the
methods differ and how they can still be considered scientific.
5.
(a) If several scientists, working independently, ask the same question and follow the
same procedures to collect data, will they necessarily come to the same
conclusions? Explain why or why not.
(b) Does your response to (a) change if the scientists are working together? Explain.
6. (a) What does the word “data” mean in science?
(b) Is “data” the same or different from “evidence” ? Explain.
7. (a) What is “data analysis” ?
(b) What is involved in doing data analysis?
158 8. After scientists have developed a theory, does the theory ever change? If you believe
that theories do change, explain why theories are important to the scientific community.
Defend your answer with examples.
PART II: DECISION MAKING QUESTIONNAIRE (DMQ)
Adapted from Bell and Lederman (2003)
Instructions
Answer the following questions using as much space as you need. Please note that there
are no “right” or “wrong” answers to these questions. I am simply interested in your
views on a number of issues about science.
Scenario I
Today, global climate change is a major environmental issue facing the United States and
the international community. According to one side, the prospect of human-induced
global warming is a near certainty, and failure to address the problem will have
catastrophic ecological consequences. According to the other side, global warming is a
hypothesis lacking scientific validation, and reducing greenhouse gas emissions will have
serious negative economic consequences.
In 1992, the United States, along with roughly 150 other nations, signed the United
Nations Framework Convention on Climate Change (FCCC) at the Earth Summit in Rio
de Janeiro. The FCCC was ratified by the US Senate in 1992 and has now been ratified
by a total of 166 nations. The ultimate objective of this treaty is to “achieve stabilization
of greenhouse gas concentrations in the atmosphere at a level thatwould prevent
dangerous anthropogenic interference with the climate system.” In line with this
objective, the most industrialized nations, including the United States, agreed to the
voluntarily aim of returning their greenhouse gas emissions back to 1990 levels by the
year 2000. However, the United States and most other industrialized nations are not on
course to meet this target. In fact, emissions in the United States are projected to be 13%
higher in the year 2000 than they were in 1990.
Because these voluntary targets have proven inadequate in curbing emissions growth,
there is now widespread agreement that legally-binding measures are necessary. The
upcoming climate conference in Kyoto, Japan, is based on the premise that the
participating nations should agree, for the first time, upon a legally-binding limit on
emissions.
159 Please answer questions 1-4 based on Scenario I.
Questions
1. Should the United States agree to legally-binding limits on greenhouse gas emissions?
Why or why not?
2. Should the United States impose special taxes on carbon dioxide emission to
encourage
energy conservation, even if this increased monthly electricity and heating bills by $25
per month? Why or why not?
3. Would you be willing to pay increased taxes in order to provide funding for research
on alternative energy resources, such as solar power and fusion reactors? Why or why
not?
4. Should the United States reduce automobile emissions by setting higher gas mileage
standards, even if this increased the average cost of a new car by $500? Why or why not?
Scenario II
Researchers are just beginning to unravel the role of diet and nutrition in the development
of cancer, or carcinogenesis. It is clear that carcinogenesis is a slow process, often taking
10–30 years. Diet may play an important role during the initiation of cancer whereby
certain foods may serve to increase detoxifying enzymes that help stop the initial
stimulation and growth of the cancer cells. At the same time, other nutrients and foods
such as fat may serve as promoters for already initiated cancer cells. Scientists have
estimated that diet is responsible for 20–40% of all cancers, perhaps as high as 70%.
Diets rich in fruits, vegetables, and fiber have consistently been shown to have a
beneficial effect on cancer. On the other hand, heavy consumption of red meats, saturated
fats, and salty foods have been linked to a variety of cancers. Other lifestyle factors
related to nutrition also appear to be associated with cancer. Obesity has been linked to a
variety of cancers, including endometrial, breast, colon, and ovarian. Alcohol
consumption has been linked to cancers of the digestive tract and liver. Conversely,
several studies have supported the beneficial aspects of physical activity, which may
reduce the risk of several types of cancer, including colon, breast, and prostate.
Questions
1. How would you rate your overall awareness of the impact of diet and related factors on
the development of cancer?
160 2. Has your awareness of the benefits of physical activity and a diet rich in fruits and
vegetables impacted how you conduct your life? If not, why not? If so, in what way(s)?
3. Do you ever base decisions about what to eat on your understandings of current
research into diet and cancer? If not, why not. If so, in what ways?
4. Do you regularly exercise? Why or why not?
5. Would you support increased legislation on foods associated with cancer, including
removing high risk foods from the market?
Scenario III
Many researchers believe that smoking accounts for a large proportion of all cancers and
as much as 30% of all cancer deaths. Cigarette smoking has specifically been implicated
as the cause of cancer of the lung, oral cavity, larynx, esophagus, bladder, kidney, and
pancreas. Additionally, the risk of developing cancer is greater for people who smoke
more and who start smoking at a younger age. Furthermore, researchers believe that
smoking may be the cause of 25–30% of all heart disease. Exposure to passive tobacco
smoke is very likely a significant cause of cancer in nonsmokers. Some scientists believe
that the increased risk could be as high as 50%. It has been estimated that thousands of
people die each year due to exposure to passive cigarette smoke.
Recently, nicotine in cigarette tobacco has been identified as a drug whose addictiveness
exceeds that of opium and heroine. In addition to this, documents have come to light that
indicate that some tobacco companies have used a variety of methods to increase the
amount and potency of nicotine in cigarette tobacco. Finally, it has been shown that many
people begin smoking as teenagers, and once started, have a very difficult time quitting.
In contrast to these claims, tobacco companies have consistently asserted that while
tobacco may be associated with increased risk for various cancers and heart disease, it
has never been proven to cause these diseases. Furthermore, to smoke or not is a free
choice that should be up to the consumer, not government agencies.
Questions
1. Given the reported dangers of cigarette smoke and its addictiveness, should legislation
be passed that would make cigarette smoking illegal? Why or why not?
2. Would you support legislation that makes it more difficult for minors to obtain
cigarettes and/or penalizes tobacco companies who target minors in their advertising?
Why or why not?
3. Do the alleged dangers of passive cigarette smoke justify banning smoking in public
places such as restaurants and bars? Why or why not?
161 Appendix E
©bioliteracy.net
Used in this dissertation with permission of developer
Accessed from https://edstools.colorado.edu/input/i-multi.php?inv=bci&cond=0
Question: 1
Many types of house plants droop when they have not been watered and quickly
"straighten up" after watering. The reason that they change shape after watering is
because ...
Water reacts with, and stiffens, their cell walls.
Water is used to generate energy that moves the plant.
Water changes the concentration of salts within the plant.
Water enters and expands their cells.
Question: 2
In which way are plants and animals different in how they obtain energy?
Animals use ATP; plants do not.
Plants capture energy from sunlight; animals capture chemical energy.
Plants store energy in sugar molecules; animals do not.
Animals can synthesize sugars from simpler molecules; plants cannot.
Question: 3
In which way are plants and animals different in how they use energy?
Animals use energy to break down molecules; plants cannot.
Animals use energy to move; plants cannot.
Plants use energy directly, animals must transform it.
162 Question: 4
How can a catastrophic global event influence evolutionary change?
Undesirable versions of the gene are removed.
New genes are generated.
Only some species may survive the event.
There are short term effects that disappear over time.
Question: 5
There exists a population in which there are three distinct versions of the gene A (a1, a2,
and a3). Originally, each version was present in equal numbers of individuals. Which
version of the gene an individual carries has no measurable effect on its reproductive
success. As you follow the population over a number of generations, you find that the
frequency of a1 and a3 drop to 0%. What is the most likely explanation?
There was an increased rate of mutation in organisms that carry either a1 or a3.
Mutations have occured that changed a1 and a3 into a2.
Individuals carrying a1 or a3 were removed by natural selection.
Random variations led to a failure to produce individuals carying a1 or a3.
Question: 6
Natural selection produces evolutionary change by ...
changing the frequency of various versions of genes.
reducing the number of new mutations.
producing genes needed for new environments.
reducing the effects of detrimental versions of genes.
Question: 7
If two parents display distinct forms of a trait and all their offspring (of which there are
hundreds) display the same new form of the trait, you would be justified in concluding
that ...
both parents were heterozygous for the gene that controls the trait.
both parents were homozygous for the gene that controls the trait.
one parent was heterozygous, the other was homozygous for the gene that controls
the trait.
a recombination event has occurred in one or both parents.
163 Question: 8
You are doing experiments to test whether a specific type of acupuncture works. This
type of acupuncture holds that specific needle insertion points influence specific parts of
the body. As part of your experimental design, you randomize your treatments so that
some people get acupuncture needles inserted into the "correct" sites and others into
"incorrect" sites. What is the point of inserting needles into incorrect places?
It serves as a negative control.
It serves as a positive control.
It controls for whether the person can feel the needle.
It controls for whether needles are necessary.
Question: 9
As part of your experiments on the scientific validity of this particular type of
acupuncture, it would be important to ...
test only people who believe in acupuncture.
test only people without opinions, pro or con, about acupuncture.
have the study performed by researchers who believe in this form of acupuncture.
determine whether placing needles in different places produces different results.
Question: 10
What makes DNA a good place to store information?
The hydrogen bonds that hold it together are very stable and difficult to break.
The bases always bind to their correct partner.
The sequence of bases does not greatly influence the structure of the molecule.
The overall shape of the molecule reflects the information stored in it.
Question: 11
What is it about nucleic acids that makes copying genetic information straightforward?
Hydrogen bonds are easily broken.
The binding of bases to one another is specific.
The sequence of bases encodes information.
The shape of the molecule is determined by the information it contains.
164 Question: 12
It is often the case that a structure (such as a functional eye) is lost during the course of
evolution. This is because ...
It is no longer actively used.
Mutations accumulate that disrupt its function.
It interferes with other traits and functions.
The cost of maintaining it is not justified by the benefits it brings.
Question: 13
When we want to know whether a specific molecule will pass through a biological
membrane, we need to consider ...
The specific types of lipids present in the membrane.
The degree to which the molecule is water soluble.
Whether the molecule is actively repelled by the lipid layer.
Whether the molecule is harmful to the cell.
Question: 14
How might a mutation be creative?
It could not be; all naturally occuring mutations are destructive.
If the mutation inactivated a gene that was harmful.
If the mutation altered the gene product's activity.
If the mutation had no effect on the activity of the gene product.
Question: 15
An allele exists that is harmful when either homozygous or heterozygous. Over the
course of a few generations the frequency of this allele increases. Which is a possible
explanation? The allele ...
is located close to a favorable allele of another gene.
has benefits that cannot be measured in terms of reproductive fitness.
is resistant to change by mutation.
encodes an essential protein.
165 Question: 16
In a diploid organism, what do we mean when we say that a trait is dominant?
It is stronger than a recessive form of the trait.
It is due to more, or a more active gene product than is the recessive trait.
The trait associated with the allele is present whenever the allele is present.
The allele associated with the trait inactivates the products of recessive alleles.
Question: 17
How does a molecule bind to its correct partner and avoid "incorrect" interactions?
The two molecules send signals to each other.
The molecules have sensors that check for incorrect bindings.
Correct binding results in lower energy than incorrect binding.
Correctly bound molecules fit perfectly, like puzzle pieces.
Question: 18
Once two molecules bind to one another, how could they come back apart again?
A chemical reaction must change the structure of one of the molecules.
Collisions with other molecules could knock them apart.
The complex will need to be degraded.
They would need to bind to yet another molecule.
Question: 19
Why is double-stranded DNA not a good catalyst?
It is stable and does not bind to other molecules.
It isn't very flexible and can't fold into different shapes.
It easily binds to other molecules.
It is located in the nucleus.
166 Question: 20
Lipids can form structures like micelles and bilayers because of ...
their inability to bond with water molecules.
their inability to interact with other molecules.
their ability to bind specifically to other lipid molecules.
the ability of parts of lipid molecules to interact strongly with water.
Question: 21
A mutation leads to a dominant trait; what can you conclude about the mutation's effect?
It results in an overactive gene product.
It results in a normal gene product that accumulates to higher levels than normal.
It results in a gene product with a new function.
It depends upon the nature of the gene product and the mutation.
Question: 22
How similar is your genetic information to that of your parents?
For each gene, one of your alleles is from one parent and the other is from the other
parent.
You have a set of genes similar to those your parents inherited from their parents.
You contain the same genetic information as each of your parents, just half as much.
Depending on how much crossing over happens, you could have a lot of one parent's
genetic information and little of the other parent's genetic information.
Question: 23
An individual, "A", displays two distinct traits. A single, but different gene controls each
trait. You examine A's offspring, of which there are hundreds, and find that most display
either the same two traits displayed by A, or neither trait. There are, however, rare
offspring that display one or the other trait, but not both.
The genes controlling the two traits are located on different chromosomes.
The genes controlling the two traits are located close together on a single
chromosome.
The genes controlling the two traits are located at opposite ends of the same
chromosome.
167 Question: 24
A mutation leads to a recessive trait; what can you conclude about the mutation's effect?
It results in a non-functional gene product.
It results in a normal gene product that accumulates to lower levels than normal.
It results in a gene product with a new function.
It depends upon the nature of the gene product and the mutation.
Question: 25
Imagine an ADP molecule inside a bacterial cell. Which best describes how it would
manage to "find" an ATP synthase so that it could become an ATP molecule?
It would follow the hydrogen ion flow.
The ATP synthase would grab it.
Its electronegativity would attract it to the ATP synthase.
It would actively be pumped to the right area.
Random movements would bring it to the ATP synthase.
Question: 26
You follow the frequency of a particular version of a gene in a population of asexual
organisms. Over time, you find that this version of the gene disappears from the
population. Its disappearance is presumably due to ...
genetic drift.
its effects on reproductive success.
its mutation.
the randomness of survival.
Question: 27
Consider a diploid organism that is homozygous for a particular gene. How might the
deletion of this gene from one of the two chromosomes produce a phenotype?
If the gene encodes a multifunctional protein.
If one copy of the gene did not produce enough gene product.
If the deleted allele were dominant.
If the gene encoded a transcription factor.
168 Question: 28
Gene A and gene B are located on the same chromosome. Consider the following cross:
AB/ab X ab/ab. Under what conditions would you expect to find 25% of the individuals
with an Ab genotype.
It cannot happen because the A and B genes are linked.
It will always occur, because of independent assortment.
It will occur only when the genes are far away from one another.
It will occur only when the genes are close enough for recombination to occur
between them.
Question: 29
Sexual reproduction leads to genetic drift because ...
there is randomness associated with finding a mate.
not all alleles are passed from parent to offspring.
it is associated with an increase in mutation rate.
it produces new combinations of alleles.
Question: 30
How is genetic drift like molecular diffusion?
Both are the result of directed movements.
Both involve passing through a barrier.
Both involve random events without regard to ultimate outcome.
They are not alike. Genetic drift is random; diffusion typically has a direction
169 Appendix F
Semistructured Interview Protocol for Human Biology and Biology Majors
Perceptions and Knowledge of Content Learning
• How would you describe your level of biology content knowledge after completing your
program?
•
Validate BCI
o Can you describe your understanding of how evolution works?
 Always selecting adv. Traits?
o
What makes DNA a good place to store information?
o
What is diffusion and why does it occur?
Perceptions and Knowledge of Inquiry
• From your experience, how would you define inquiry in biology?
•
What experiences helped you develop that understanding?
•
Validate VOSI
o What is an experiment?
o
Define data. Is it the same as evidence? What’s the difference?
o What is a theory?
Other VOSI items
Perceptions and Knowledge of Socioscientific Issues
• How well do you feel your program has prepared you to understand and make decisions
on controversial issues related to biology (issues that have social impact)? Can you give
some examples?
•
Validate DMQ
o From scenario 1: Recent science reports have argued that the phenomenon of
global warming may be due primarily to landscape transformations from forest
and grassland to concrete roads and buildings, rather than carbon emissions. In
view of this conflicting evidence, how could you make decisions about regulating
carbon emissions?
o
From scenario 2: How do you make dietary decisions when nutritionists have
repeatedly altered their recommendations, as in the case of the inclusion of
Omega-3 fatty acid supplements in the diet?
170 o
From scenario 3: How would you make decisions considering some scientists’
assertions that the links between tobacco and cancer have never been proven?
Perceptions of Program
• Why did you choose to be a student in your program?
•
How would you describe the primary teaching strategies used in your program?
•
Of these aspects, what was most helpful to your learning?
•
What did you find unhelpful or difficult?
•
Have you had any classes that use non-traditional approaches?
•
Have you had any classes that have helped you to explore different perspectives toward
biology issues with social implications?
•
How would you describe the level of community in your program?
•
Were there any opportunities that were available or that you took advantage of, that
enhanced your experience as a Human Biology/biology major?
Future Plans, Impact of Program
• What are your plans after graduation?
•
Would you say your program has helped you meet your goals? How?
•
How would you describe your development in your program? How have you changed
over the past 4 years as a result of being a biology/HUBI major?
171 Appendix G
Coding Scheme for the Modified VOSI
Question
1. What types of activities do
scientists do to learn about
the natural world? Be specific
about how they go about their
work.
Addresses Processes of
inquiry
2. What scientists choose to
study and how they learn
about the natural world may
be influenced by a variety of
factors. How do scientists
decide what and how to
investigate? Describe all the
factors you think influence
the work of scientists. Be as
specific as possible.
Addresses Purpose of inquiry
3. (a) Write a definition of a
scientific experiment. A
scientific experiment is……
Addresses Meaning of
experiment
Response Codes
Definition
QUESTION
Begin with/center investigation in question
DIFF METHODS
Different environments require different
methods; field vs. wild
DIFF SCIENCES
Different fields of inquiry (social sciences vs.
biological/physical require different
approaches)
CONTROL
Some investigations are controlled, others
involve observation of uncontrolled natural
process
EXPERIMENTAL
Purely experimental conception; controlled
environment
SCI METHOD
Explicitly states that scientists use “scientific
method”
GENERAL INQUIRY
searching for information about natural world
SCIENCE PROCESS
SKILLS
at least one: hypothesis, data collection,
analysis, etc.
SOCIAL SCIENCE
PROCESSES
INTERNAL
at least one: interview, survey, etc.
Reasons internal to scientist-interest,
personal/family reasons, prior experiences,
influences on personal background
Reasons external to scientist other than
practical concerns-current trends, interest of
society, current influences of other people
EXTERNAL
Practical concerns or limitations-funding,
resources, time constraints
PRACTICAL
CONTROL
Control and manipulate variables
REPLICABLE
Must be replicable
GENERAL INQUIRY
Searching for answers/new knowledge
SCI METHOD-
States that the scientific method must be
followed
TESTS HYPOTHESIS
Hypothesis is tested
VALIDITY/
Has validity, accuracy, regulation, or
172 ACCURACY
extensive planning
CAUSE-EFFECT
WHOLE PROJECT
Looks for causal relationships
Uses example of whole project or scientific
endeavor (ex/ cancer research, discover gene,
etc.)
3. (b) Give an example from
something you have done or
heard about in science that
illustrates your definition of a
scientific experiment.
CLASS
Describe class experiment
RESEARCH GROUP
Describe controlled lab/field experiment
SOC SCI
Describe social science project
experiment
3. (c) Explain why you
consider your example to be a
scientific experiment.
PROCEDURE
Only procedural part of a project, ex/ gel
electrophoresis
with 3a
CONSISTENT
INCONSISTENT
experiment
4. (a) Is there one scientific
method or set of steps that all
investigations must follow to
be considered science? If you
answered “yes,” answer (b)
below. If you answered “no,”
answer (c) below.
Addresses
Definition/existence of
scientific method
4. (b) If you think there is one
scientific method, what are
the steps of this method?
Addresses Definition of
scientific method
YES
NO
QUESTION
includes questions
OBSERVE
includes observation
BG
includes background research
HYPOTHESIS
includes hypothesizing
DATA
includes data collection/methods
ANALYSIS
includes analysis
CONCLUSIONS
includes development of conclusion/theory
REVISE/REPEAT
revise hypothesis and continue research
COMMUNICATE
presenting or publishing
GENERAL INQUIRY
Scientific method viewed as general
information-gathering
FOLLOWS STEPS
Certain steps must be followed
173 4. (c) If you think that
scientific investigations can
follow more than one
method, describe two
investigations that follow
different methods. Explain
how the methods differ and
how they can still be
considered scientific.
Addresses Explanation of
multiple methods
SOME VARIATION
Scientists vary steps or order of steps
DIFF METHODS
Methods vary depending on project
CONTROL
Controlled environment vs. “wild” (ability or
desire to control)
EXPLORATORY/
CONFIRMATORY
Interventionist or observational
DIFF METHODS
Different science protocols, materials for
different science subject matter
DIFF SCIENCES
Natural and physical sciences vary from social
sciences
DIFF ORDER OF
METHODS
Scientists may do steps in different orders
INVESTIGATE
Scientific if answers are being sought
NAT WORLD
Deal with natural world
SYSTEMATIC
Rigorous or regulated
RELIABLE
YES
Others should see same results
SAME PROCEDURES
Scientists will use the same procedures; fully
replicable
NO
5. (a) If several scientists,
working independently, ask
the same question and follow
the same procedures to
collect data, will they
necessarily come to the same
conclusions? Explain why or
why not.
Addresses Impact of
researcher on science
Identification/resolution of
anomaly
Subjectivity
ERROR
There will still be differences in error or
accuracy
DIFF DATA
Uncontrollable factors or different
environments lead to different data
DIFF METHODS
Scientists will still use different procedures
DIFF INTERPRETATIONS
Scientists interpret results differently or have
different perspectives
CAN COME CLOSE
Scientists should have similar results
MAYBE
Elements of both yes and no answers
CHANGE
SAME DATA
If working together data will be the same
174 5. (b) Does your response to
(a) change if the scientists are
working together? Explain.
Addresses
Identification/resolution of
anomaly
subjectivity
SAME PROCEDURES
Procedures will be the same
REACH
CONSENSUS
Scientists will challenge and resolve
differences
REDUCE ERROR
Working together reduces differences
resulting from error
NO
Scientists still interpret results differently.
They may disagree or have personal biases.
DIFF DATA
Uncontrollable factors still result in different
data.
DIFF METHODS
MORE LIKELY
Scientists will still use different methods
MAYBE CHANGE
SAME
DATA/METHODS
INFO COLLECTED
6. (a) What does the word
“data” mean in science?
Addresses Difference between
data and evidence
Information collected in experiments or
observations
RESULTS
Uses only the term, “results”
NUMBERS
Data must be quantitative
QUANT/QUAL
Data can be quantitative or qualitative
SUPPORTS IDEA
Data supports a hypothesis or idea
ANALYSES
SAME
Data has been analyzed
BOTH SUPPORT
Both support an idea or answer a question
DIFF
6. (b) Is “data” the same or
different from “evidence” ?
Explain.
Addresses Difference between
data and evidence
EVIDENCE
SUPPORTS
Evidence supports or proves an idea, or
explains or interprets a situation
EVIDENCE IS MORE
CERTAIN
Evidence is more definite, certain, conclusive,
or factual
EVIDENCE IS LESS
PRECISE
Evidence is less “correct,” “scientific,” exact,
or is biased
EVIDENCE IS
GENERALIZA-TION
Evidence is a generalization, abstraction,
compilation, or analysis of data
175 DATA IS NUMBERS
Data is always quantitative
DATA CAN BE
EVIDENCE
State data can be evidence, but not how they
are different
EVIDENCE CAN
CHANGE
Evidence is less permanent
NO EVIDENCE IN
SCIENCE
There can be no such thing as evidence in
science because there is no proof in science.
EVIDENCE FROM
OTHER SOURCES
Evidence can come from other sources than
the current inquiry
EV IS COMPARED
Evidence is compared to other evidence
All data is useful, evidence may be discarded
EVIDENCE MAY BE
DISCARDED
NO
THEORY IS LAW
Theory and law are the same-both do not
change.
YES
NEW DATA (NEW
TECH)
NEW INTERPRETATIONS
8. After scientists have
developed a theory, does the
theory ever change? If you
believe that theories do
change, explain why theories
are still important to the
scientific community. Defend
your answer with examples.
Addresses Tentativeness of
theory
Purpose of theory
Availability or discovery of new data leads to
change (New technology leads to change)
Theories change through new interpretations
of existing data
SCIENCE CHANGES
General statement without elaboration
SCIENTISTS REVISE
OWN THEORIES
Changing of theories is an individual
process—no community involved
BEST WORKING
EXPLANATION
It is the best explanation for our current
understanding of a phenomenon
THEORY LESS
“TRUE” THAN LAW
Theory is lower in hierarchy of confidence
MAY REACH FINAL
STATE
Theories can eventually become laws or be
proved true.
CUMULATIVE VIEW
Theories are built upon only to become better
or more complex
FALSIFICATION
VIEW
Theories are put forth to be retested or
falsified
IDEAS FOR NEW
Theories provide ideas for future inquiry or
176 INQUIRY
basis for revision of understanding
Theories promote discussion of ideas in
scientific communities
ENCOURAGE
DISCUSSION
Theories provide record of how thinking has
changed over time
PROVIDE
HISTORICAL
RECORD
177 Appendix H
Methods Matrix
178 179 VITA
Jennifer Lynne Eastwood
July, 2010
University Address:
Science Education Program
Curriculum and Instruction
W. W. Wright Education Building
Indiana University
201 N. Rose Avenue
Bloomington, Indiana 47405
Home Address:
2473 S. Woolery Mill Drive
Bloomington, Indiana 4740tr3
(812) 272-9079
jvanduse@indiana.edu
EDUCATION
2005-present
Ph.D., Science Education (expected completion date May, 2010), Curriculum and
Instruction Department, Indiana University, Bloomington, Indiana.
• Advisor and Doctoral Committee Chair: Dr. Robert D. Sherwood
• Dissertation title: The Effects of an Interdisciplinary Undergraduate Human Biology
Program on Socioscientific Reasoning, Content Learning, and Understanding of
Inquiry.
• Minor: Anatomy and Cell Biology
2002-2005
Master of Sciences, Anatomy and Cell Biology, Medical Sciences Program, Indiana
University, Bloomington, Indiana.
• Thesis title: “Proteomic based identification of epidermal markers for the nipple.”
• Advisor, Dr. John Foley
1997-2001
Bachelor of Arts, Biology, Truman State University, Kirksville, MO.
• Minor, French
TEACHING
2009-present
Associate Instructor, A464, Human Tissue Biology, Indiana University Bloomington, IN.
Completed one lab section, currently teaching two sections: Introduce histological slides
and staining techniques, conduct microscope based labs, and develop practical exams.
2009-2010
Mentor to Pre-service Teachers, Saturday Science, Indiana University, Bloomington, IN.
Provide support and feedback in the development and teaching of six-week informal
science courses for K-2 students from the community.
2009
Associate Instructor, A215, Basic Human Anatomy, Indiana University, Bloomington, IN.
• Taught two sections: Conducted lab, review, and exam sessions in undergraduate
gross anatomy and histology.
• Provided introductions and one-on-one assistance to students in understanding
form/function relationships, and conducted small group demonstrations with human
donors.
2007-2009
Associate Instructor, Q200, Introduction to Scientific Inquiry, Indiana University
Bloomington, IN.
• Taught five sections of a lab-based introductory science course for pre-service
elementary teachers focusing on application of scientific inquiry and the nature of
science.
• Collaborated with instructors to develop inquiry-based activities and assessments.
2005
Associate Instructor, P312, Learning: Theory into Practice, Indiana University,
Bloomington, IN.
Developed and taught two sections of a course on Educational Psychology and Learning
Sciences theory for pre-service secondary teachers.
2003-2006
Associate Instructor, A215, Basic Human Anatomy
• Description above (2009); 13 sections
• Conducted and presented educational research to improve A215 lab.
2001-2002
Secondary Biology Teacher, Crawford ISD, Crawford, Texas.
• Taught 7th grade Life Science and 10th grade Biology.
• Served as Crawford ISD yearbook co-sponsor.
2000
Teaching Assistant, General Biology, Truman State University, Kirksville, MO.
Provided assistance in grading, course organization, and assisted students in lab activities.
2000
Teaching Assistant, Comparative Anatomy, Truman State University, Kirksville, MO.
Assisted students in animal dissections and developing lab practical exams.
RESEARCH ACADEMIC APPOINTMENTS
2008-2009
Graduate Educational Consultant, Indiana University Bloomington Libraries,
Bloomington, IN.
• Provided support with assessment development, project evaluation, and Human
Subjects compliance for project on integration of ACRL Information Literacy
Competency Standards for Higher Education into interdisciplinary courses including
Biology and Gender Studies.
• Project Title: “Information Fluency for the Disciplines,” 2007 SoTL Leadership
Grant.
2008
Research Assistant, Science Education, Indiana University, Bloomington, IN.
Assisted faculty on grant applications, data collection, data analysis, and manuscript
writing for various projects.
PUBLICATIONS
Akerson, V., Buzzeli, C., Eastwood, J. (2010). The Relationship Between Preservice Early Childhood
Teachers’ Cultural Values and their Perceptions of Scientists’ Cultural Values. Journal of Science Teacher
Education, 21, 205-214
Buck, G., Cook, K., Quigley, C., Eastwood, J., & Lucas, Y. (2009). Four profiles of urban, low SES,
African-American girls' attitudes toward science: A sequential explanatory mixed-methods study. Journal
of Mixed Methods Research, 3, 386-410.
Eastwood, J. (2007). Standardizing Quality in a Large Undergraduate Anatomy Lab. HAPS-Educator,
Summer Edition.
Eastwood, J. Offutt, C. Menon, K. Keel, M. Hrncirova, P. Novotny, M.V., Arnold, R., Foley, J. (2007).
Identification of markers for nipple epidermis: changes in expression during pregnancy and lactation.
Differentiation. 75, 75-83.
MANUSCRIPTS IN PREPARATION OR REVIEW
Eastwood, J. L., & Schlegel, W. M. Electronic Reflection by Student Teams Facilitates and Provides
Evidence of Team-Based Learning Process. Advances in Physiology Education. In preparation.
Akerson, V., Buzelli, C., & Eastwood, J. ‘Strangers in a strange land’: Bridging the gap between
preservice early childhood teachers’ cultural values and their perceptions of values held by scientists.
Journal of Research in Science Teaching. In Review.
Akerson, V.A., Donnely, L., Riggs, M., & Eastwood, J. Supporting preservice elementary teachers’ nature
of science instruction through a community of learners. Journal of Science Teacher Education. In Review.
CONFERENCE PROCEEDINGS (PUBLISHED)
Buck, G. A., Cook, K., Quigley, C., Eastwood, J., Lucas, Y. (2009). Exploring how urban AfricanAmerican girls position themselves in science learning: A sequential explanatory mixed-methods study.
Paper Presented at National Association for Research in Science Teaching (NARST), Garden Grove, CA.
Akerson, V.A., Donnely, L., Riggs, M., & Eastwood, J. (2009). Supporting Preservice Elementary
Teachers’ Nature of Science Instruction Through a Community of Learners. Paper Presented at National
Association for Research in Science Teaching (NARST), Garden Grove, CA.
Teachers’ Nature of Science Instruction Through a Community of Learners. Paper presented at American
Educational Research Association (AERA), San Diego, CA.
PRESENTATIONS AT ACADEMIC MEETINGS
Eastwood, J., Cook, K., Sherwood, R., & Schlegel, W. (2010). “Not Simply What’s the Science, but How
Does It Affect People, and Why Is That Important?” Effects of an Interdisciplinary Human Biology
Program Focused on Socioscientific Reasoning. Research presentation, National Association for Research
in Science Teaching (NARST), Philadelphia, PA.
Akerson, V., Buzelli, C., & Eastwood, J. (2010). ‘Strangers in a Strange Land’: Bridging the Gap between
Preservice Early Childhood Teachers’ Cultural Values and their Perceptions of Values Held by Scientists.
Reasearch presentation, National Association for Research in Science Teaching (NARST), Philadelphia,
PA.
Eastwood, J. L., & Schlegel, W.M., (2009). Electronic Reflection by Student Teams Facilitates and
Provides Evidence of Team-Based Learning Process. Research presentation, International Society for the
Scholarship of Teaching and Learning (ISSOTL), Bloomington, IN.
Eastwood, J. L. (2009). Reflecting Student Learning in a Team-based and Case-based Physiology Class:
the Developmental and Representational Roles of Reflective Activities. Research presentation, Indiana
University Science Education Research Symposium, Bloomington, IN.
Buck, G.A., Cook, K.L., Quigley, C.F., & Eastwood J. L. (2009) Exploring how urban African-American
girls position themselves in science learning: A sequential explanatory mixed-methods study. Research
presentation, National Association for Research in Science Teaching (NARST), Garden Grove, CA.
Akerson, V., Buzelli, C., & Eastwood, J. (2009). The Relationship between Preservice Early Childhood
Teachers’ Cultural Values and the Cultural Values they Believe that Scientists Hold. Research presentation,
American Educational Research Association (AERA), San Diego, CA.
Teachers’ Nature of Science Instruction Through a Community of Learners. Research presentation,
National Association for Research in Science Teaching (NARST), Garden Grove, CA.
Teachers’ Nature of Science Instruction Through a Community of Learners. Research presentation,
American Educational Research Association (AERA), San Diego, CA.
Buck, G., Amirshokoohi, A., Beeman-Cadwallader, N., Caylor, B., Eastwood, J., Nargund, V., Schmelz,
R., Sher, M. (2007). Making Inquiry into Chemistry Discernible to Pre-Service Teachers. Workshop
presented at Annual Meeting of the School Science and Mathematics Association, Indianapolis, IN.
Eastwood, J. & Schlegel, W. M. (2006). Creating a Model for Pedagogies of Uncertainty. Research
presentation, International Society for the Scholarship of Teaching and Learning (ISSOTL), Washington
D.C.
French Doubleday, A. & Eastwood, J. (2006). Standardizing Quality in a Large Undergraduate Anatomy
Lab. Workshop presented at the Annual Meeting of the Human Anatomy and Physiology Society (HAPS),
Austin TX.
Eastwood, J., Schlegel, W., Duffy, T. (2006). Perceptions of Equitable Contribution and Team
Performance in a Case-Based Human Physiology Course. Indiana University Scholarship of Teaching and
Learning Spring Poster Session, Bloomington, IN.
Eastwood, J., Hrncirova, P., Arnold, R., Foley, J.G. (2005). Proteomic Based Identification of Epidermal
Markers for the Murine Nipple. Poster presented at the Annual Meeting for the Society for Investigative
Dermatology, St. Louis, MO.
Eastwood J. & French Doubleday, A. (2005). Tips from the Trenches: an Associate Instructor’s
Perspective on Teaching Human Anatomy Lab. Workshop presented at the Annual Meeting for the Human
Anatomy and Physiology Society (HAPS), St. Louis, MO.
HONORS AND SCHOLARSHIPS
Medical Sciences Outstanding Associate Instructor Award, Indiana University, 2010
First Year Graduate Student Fellowship, Medical Sciences, Indiana University, 2002.
Cum Laude, Truman State University, 2001.
Presidential Scholarship, Truman State University, 1997.
Combined Ability Scholarship, Truman State University, 1997.
GRANT WRITING AND AWARDS
Indiana University Graduate School Grant in Aid of Doctoral Research. Title: The Impacts of an
Interdisciplinary Undergraduate Human Biology Program on Socioscientific Reasoning, Content Learning,
and Understanding of Inquiry. February, 2010. $1000: Funded.
Indiana University Graduate and Professional Student Organization Travel Award. Title: The Impacts of an
Interdisciplinary Undergraduate Human Biology Program on Socioscientific Reasoning, Content Learning,
and Understanding of Inquiry. February, 2010. $250: Funded.
Spencer Foundation Dissertation Fellowship. Title: Can an Interdisciplinary Program Promote Students’
Development of Content Knowledge, Inquiry Understanding, and Ethical Reasoning? A Mixed-Methods
Study of an Undergraduate Human Biology Program. 2009-2010. $25,000: Unfunded.
NSF Discovery Research K-12. Title: Indiana University DR-K12 Resource Network Proposal. P.I.s:
Robert Sherwood, Catherine Brown, Robert Goldstone, & Jonathan Plucker. January 2008. $4,997,821:
Unfunded.
Role: assisted in research and preparation of grant.
CURRENT MEMBERSHIPS IN PROFESSIONAL ORGANIZATIONS
National Association of Research in Science Teaching (NARST)
International Society for the Scholarship of Teaching and Learning (ISSOTL)
Human Anatomy and Physiology Society (HAPS)
PROFESSIONAL SERVICE
2009
Conference Reviewer, National Association of Research in Science Teaching.
2009
Conference Reviewer, International Society for the Scholarship of Teaching and
Learning
2005-2009
Editorial Committee, Human Anatomy and Physiology Society
Edited quarterly publications and review educational research submissions.
2006
Conference Reviewer, National Association of Research in Science Teaching.
2006
International Conference of the Learning Sciences Session Coordinator
• Collaborated with conference directors in program planning and session
organization.
• Served as a liaison and session host for presenters.
2005-2006
Learning Sciences Student Representative.
• Voiced student concerns at faculty meetings.
• Facilitated communication between faculty and students.
2001
Student Director for Regional Science Olympiad Competition, Kirksville, MO.
• Worked with professors and secondary teachers to organize and facilitate the
competition for middle and high school students.
• Developed and conducted a Life Science event in the competition.
• Co-sponsored an event at the 2001 Missouri state-wide competition.
COMMUNITY SERVICE
2008-present
Global Women’s Gathering
Co-organize weekly meetings for international women to help them practice English,
learn about the community, and develop relationships.
2007
English Teaching, Tbilisi, Georgia, 1/07-8/07.
• Taught children’s English courses at Tbilisi Evangelical Baptist Church and a local
after-school program.
• Provided advanced lessons and English conversation practice for adults.
PROFESSIONAL REFERENCES
Dr. Robert Sherwood, Professor of Science Education
Ph.D. Advisor
W.W. Wright Education Building Room 2070
Indiana University
Bloomington, IN 47405
Phone : (812) 856-8154
Email: rdsherwo@indiana.edu
Dr. Valarie Akerson, Associate Professor of Science Education
Ph.D. committee member and research mentor
Indiana University
Dept. of Curriculum and Instruction
201 North Rose Avenue
812-856-8140
Email: vakerson@indiana.edu
Dr. Whitney Schlegel, Associate Professor of Biology
Ph.D. committee member and research mentor
Jordan Hall 300
Indiana University
Phone: (812) 855-7116
Email: wreilly@indiana.edu
Dr. Valerie Dean O’Loughlin, Associate Professor of Anatomy, Director of Undergraduate Human
Anatomy
Mentor in teaching
Jordan Hall 105
Indiana University
Phone: (812)855-7723
Email: vdean@indiana.edu

dissertation final - Gradworks

Transcription

Similar documents

276 SSi ::: Chaparral

SAMPLE MCAS High School Biology Reference Sheet

Chaparral Ssi 230 - {ModelName} Charter Brochure

Karen K. Resendes Westminster College New Wilmington, Pa

10 species of sea anemones

Form SSA-1171-KIT

Read More Here - Syndicated Solutions, Inc.

Honors Biology - Grand Haven High School

Systems Biology Ireland (University College Dublin) and Biomedical Diagnostics Institute

Biology by Design: From Vibrating Insoles to Synthetic Gene Networks