An Analysis of Instructor Extraversion and Student Learning Style

Transcription

Walden University
ScholarWorks
Walden Dissertations and Doctoral Studies
2015
An Analysis of Instructor Extraversion and Student
Learning Style
Celeste Christine Bazier
Walden University
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Walden University
College of Social and Behavioral Sciences
This is to certify that the doctoral dissertation by
Celeste Bazier
has been found to be complete and satisfactory in all respects,
and that any and all revisions required by
the review committee have been made.
Review Committee
Dr. Peggy Gallaher, Committee Chairperson, Psychology Faculty
Dr. Carl Valdez, Committee Member, Psychology Faculty
Dr. Virginia Salzer, University Reviewer, Psychology Faculty
Chief Academic Officer
Eric Riedel, Ph.D.
Walden University
2015
Abstract
An Analysis of Instructor Extraversion
and Student Learning Style
by
Celeste C. Bazier
MA, University of Texas San Antonio, 2002
BA, Purdue University, 1981
Submitted in Partial Fulfillment
of the Requirements for the Degree of
Doctor of Philosophy
General Educational Psychology
Walden University
February 2015
Abstract
An instructor’s personality may influence his or her teaching strategies and instructional
style. Correspondingly, a student with a particular learning style may respond more
readily to one teacher personality type as opposed to another. This quantitative research,
guided by theories of personality and learning, examined the relationship between
instructor level of extraversion and student visual, auditory, or kinesthetic learning
modalities in a community college setting. A cross-sectional correlation design was
implemented. Three hundred and two students from a community college in the
southwestern United States were asked to select an instructor (past or present) they
thought taught effectively and complete an observer-rated extraversion scale from the Big
Five Inventory on the selected instructor. The students also self-reported their learning
style using the Barsch Learning Style Inventory along with a demographic questionnaire.
Upon establishing the dominant learning style of each student, a one-way ANOVA was
conducted to analyze instructor’s extraversion level with student’s dominant style of
learning. Pearson correlations were examined to determine relationships between
instructor extraversion and auditory, visual, and kinesthetic learning style scores. While
findings did not indicate a positive correlation between instructors’ degree of
extraversion and students’ visual learning style scores, it did show that visual learners
rated effective instructors higher on the trait of extraversion than did auditory or
kinesthetic learners. In addition, further analyses indicated that auditory and kinesthetic
learning style scores negatively correlated to an instructor’s level of extraversion. This
study’s results emphasize the importance of considering both instructors’ personality
traits and students’ learning styles in fostering an advantageous learning environment.
An Analysis of Instructor Extraversion
and Student Learning Style
by
Celeste C. Bazier
MA, University of Texas San Antonio, 2002
BA, Purdue University, 1981
Submitted in Partial Fulfillment
of the Requirements for the Degree of
Doctor of Philosophy
General Educational Psychology
Walden University
February 2015
Dedication
To my daughters, Tiana and Cheyenne, you are my reason for continuing to seek
knowledge. You are my strength, my reassurance and my hope for the future.
To my husband, Derrick, who has both willingly and unwittingly inspired me in this
endeavor. I love you all. To my Mom and Dad, who have passed through this life, it was
you who taught me the value of education, through your words and your deeds. I thank
you.
Acknowledgments
To Dr. Gallaher, my advisor, my advocator, my critic, and mentor, I am grateful
for your instruction and patience throughout this process. Your guidance has been
invaluable to me. Thank you Dr. Valdez, your advice and encouragement has been deeply
appreciated and vital to my understanding of this process. My thanks to Dr. Billimek and
Dr. Wood who assisted me with the approval process. Also my thanks to a Ms. Linda
Bates who was instrumental in encouraging instructors and their students to take part in
this research.
Table of Contents
List of Tables................................................................................. ......................................v
Chapter1: Introduction to the Study .....................................................................................1
Preface1
Overview ........................................................................................................................1
Background ....................................................................................................................5
Statement of the Problem .............................................................................................10
Purpose of the Study ............................................................................................. 11
Research Hypotheses ...................................................................................................12
Definitions....................................................................................................................13
Theoretical Constructs .......................................................................................... 13
Definition of Terms............................................................................................... 15
Significance..................................................................................................................15
Nature of the Study ......................................................................................................17
Assumptions and Limitations ......................................................................................17
Summary ......................................................................................................................18
Chapter 2: Literature Review .............................................................................................21
Introduction ..................................................................................................................21
Instructional Models ....................................................................................................24
Jung and Extraversion ........................................................................................... 26
Eysenck and Extraversion ..................................................................................... 30
i
The Evolutionary Basis for Extraversion .....................................................................32
The Heritability of Extraversion ..................................................................................35
Myers-Briggs Assessment ...........................................................................................36
Dimensions of Extraversion .........................................................................................37
The Big Five Personality Theory .......................................................................... 37
Eysenck Personality Inventory/Questionnaire ...................................................... 40
Research on Personality and Learning .........................................................................41
Extraversion: A Closer Look .......................................................................................43
Research on Teacher Personality and Student Outcomes ..................................... 44
Gardner’s Theory of Multiple Intelligences ......................................................... 47
Learning Styles ............................................................................................................50
VAK model. .......................................................................................................... 51
VARK Model. ....................................................................................................... 54
Genetic Component of Learning Styles .......................................................................55
Learning Style Preferences ..........................................................................................56
Learning Styles Assessments .......................................................................................59
Limitations ...................................................................................................................60
Implications of Past Research on Present Research ....................................................61
Summary ......................................................................................................................62
Chapter 3: Methodology ....................................................................................................64
Introduction ..................................................................................................................64
Purpose of the Study ....................................................................................................64
ii
Research Design and Approach ...................................................................................65
Setting and Sample ......................................................................................................66
Participants............................................................................................................ 66
Administering Procedures ..................................................................................... 68
Instrumentation ............................................................................................................69
BFI
................................................................................................................... 69
BLSI ................................................................................................................... 70
Demographics ....................................................................................................... 72
The Research Hypotheses ............................................................................................72
Data Analysis ...............................................................................................................73
Ethical Considerations .................................................................................................75
Summary ......................................................................................................................75
Chapter 4: Results ..............................................................................................................77
Introduction ..................................................................................................................77
Data Collection ............................................................................................................77
Research Questions and Variables Used......................................................................82
Descriptive Statistics....................................................................................................85
Cronbach Alpha Reliability Estimation .......................................................................86
Hypothesis #1: Statistical Results ................................................................................89
Hypothesis# 2 through #4: Statistical Results .............................................................90
Summary ......................................................................................................................90
Chapter 5: Discussion, Conclusions, and Recommendations ............................................92
iii
Introduction ..................................................................................................................92
Interpretation of Findings ............................................................................................93
Research Question 1 ............................................................................................. 93
Methodological, Theoretical and Empirical Implications .........................................100
Implications for Social Change ..................................................................................101
Recommendations for Practice ..................................................................................103
Recommendations for Further Study .........................................................................104
Conclusion .................................................................................................................106
References ..................................................................................................................111
Appendix A: Consent Form .......................................................................................141
Appendix B: Big Five Inventory-Observer rating Scale............................................142
Appendix C: Barsch learning Style Inventory ...........................................................144
Appendix D: Demographic ........................................................................................146
iv
List of Tables
Table 1. Demographic Variables……………………………………………….……..…80
Table 2. Means and Standard Deviations……………………………………….……….85
Table 3. Internal Consistency Values (Cronbach α)…………………………….……….85
Table 4. Spearman Correlations: Age/Learning Style……………………….……..........87
Table 5. Independent Samples t Test: Gender/ Learning Style……………….................88
Table 6. One-Way Analysis of Variance: Race/Ethnicity/ Learning Style……….......... 88
Table 7. One-Way Analysis of Variance: Hypothesis 1……………………………........89
Table 8. Pearson Correlations: Extraversion/Learning style…………………….…......90
v
1
Chapter 1: Introduction to the Study
Preface
Acquiring, dispensing, and digesting knowledge has been a lifelong journey of
mankind. Great thinkers in past times have pondered the question of how thought
processes occur, why people think the way they do, and how people arrive at conclusions
and absolutes. Socrates proclaimed, “I cannot teach anybody anything. I can only make
them think” (Socrates, n.d.). It is the process of thinking, doubting, accepting truisms,
and rejecting ideas that has challenged pedagogical practices throughout history (Marin
& Halpern, 2011). According to Trudeau and Barnes (2011), the commonalities and
differences among learners and instructors is instrumental in the delivery and absorption
of knowledge, the coaxing of creativity, and the development of the human race.
Overview
This dissertation’s significance is established within the personality trait of
extraversion and its effect on different modalities of learning. The assertion is that certain
parts of personality, being relatively unchanging after age 30 (Terracciano, McCrae, &
Costa, 2010), will produce automatic and natural actions, reactions, and responses that
capture the attention of a particular learning style. In this chapter, the purpose of this
research is recognized through an understanding of the community college population
and its instructors. Detailed descriptions of the problem along with hypotheses are
offered in an effort to identify and modify the subtle nuances contributing to the
perplexing teacher/learner relationship. There is much controversy concerning the trait of
extraversion. Goldberg (1993) and Wiggins (1992) both attributed the characteristic of
2
dominance to be associated with the extraversion trait, while McCrae and Costa (1994)
described a medium between dominance and warmth, with the dominance trait being
slightly more significant. Extraversion’s identity spans across a variety of descriptions.
McCrae and John (1992) proposed six dimensions of extraversion as warmth,
gregariousness, confidence, action oriented, excitement seeking, and positive sensations.
Wilt and Revelle (2008) suggested adjectives such as boastful, arrogant, garrulous,
talker, and chatty. On a continuum, those traits, at their optimal, would represent one
end, while the traits of quiet, reserved, shy, and silent would represent the other end (Wilt
and Revelle, 2008).
A continuing debate within academia is the extent to which students should
acclimate to their environment and the extent to which the environment should acclimate
to them. Apart from the students’ personality traits, which have shown to be correlated to
different learning styles (Komarraju, Karau, Schmeck, & Avdic, 2011), it is the ability of
the instructor to penetrate the intellectual psyche that is in question (Bean, 2005). Some
have advocated for matching learning styles to teaching methods (Zhang, Sternberg, &
Fan, 2013). Charkins, O’Toole, and Wetzel (1985) contended that various methods of
teaching have minimum effect on student learning and controlling for the differences in
student learning styles is crucial. They emphasized student learning may be aided or
hindered by a teacher’s instructional technique and therefore some students’ gains may be
counterbalanced by other students’ losses.
In contrast, Pashler, McDaniel, Rohrer, and Bjork (2008) recognized several
studies that disputed the premise of matching learning styles to teaching methods and
3
concluded that the evidence for this method of instruction was lacking in merit. Instead,
emphasis should be placed on examining evidenced-based strategies that improve
learning and memory in general. Moreover, the researchers acknowledged the probability
that not all learning style modalities have been tested.
Controlling for the differences in learning styles is approachable by various
methods. I propose one method is by adjusting classes to accommodate particular
learning styles and appointing instructors to those classes who are a best fit through their
level of extraversion and other variables. Two factors that determine effective instruction
are the knowledge of content and the ability to convey this knowledge (Shulman, 1986).
According to Terregrossa, Englander, Zhaobo, and Wielkopolski (2012), academic
achievement is derived from the teaching effectiveness of the instructor. Their study
consisted of first year economic and accounting students with a relatively low number of
participants (N = 61). Findings supported the assertion that learning styles may differ
according to subject area, all other variables remaining constant. The kinesthetic variable
in the economic class was positively correlated while the visual and auditory variables
were negatively correlated to academic achievement. In contrast, the auditory component
for accounting students had a positive correlation to academic achievement while the
tactile/kinesthetic learner was negatively correlated, implying students may be partial to a
particular learning style if he or she is inclined to study in a specific subject area.
Furthermore, Dunn et al. (2009) contended instruction should match the learning
style of the student in order to optimize learning. Terregrossa et al. (2012) identified
extraverted instructors as performing better than introverts when teaching takes place in
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the presence of students, and yet, Baker and Bishel (2006) found extraverts deficient in
processing ability, noting that extraverts are less motivated to deliberate over concepts.
Instructors who are introverts, preferring abstract ideas (Capretz, 2003), may assume that
students need a great amount of autonomy when working.
Extraverts tend to enjoy being around other people and delight in lively
conversations. According to Terregrossa et al. (2012), extraverted instructors are talkative
and may monopolize conversations. Instructors with an ample amount of the extraversion
trait are sociable and outgoing (Hills & Argyle, 2001). These are the instructors who
encourage conversations in the classroom (Terregrossa et al., 2012). They invite
constructive debate and may deviate from typical conversations (Terregrossa et al.,
2012). They thrive in the art of persuasion and entertainment (Terregrossa et al., 2012).
This tendency may be desirable for an auditory learner who may fixate on the instructor’s
every word. Extraverted instructors are also risk takers (Nettle, 2004). It is not
inconceivable that they may present unproven theories or erroneous proclamations in
order to awaken or challenge an action or reaction from their students. They exercise,
play sports, and are generally more active than introverts (Nettle, 2004). According to
Capretz, (2003), they are attentive to the external world. This type of behavior may be
appealing to the kinesthetic learner who gravitates toward learning activities involving
movement and hands-on training (Dunn, Dunn, & Price, 1985).
The instructor lacking in the extraversion trait is serious and reserved (Hills &
Argyle, 2001), preferring solitude, a few close friends, and tranquility. This temperament
implicates an intensely thoughtful instructor: expressing opinions sparingly, choosing
5
words carefully, and delivering content purposefully. According to Hills and Argyle,
(2001), conversing is not an introvert’s strength; therefore visual learners could be partial
to an introverted instructor’s demonstrations and graphic explanations (Dunn et al.,
1985). Students may be captivated by slide shows and guest speakers, leaning toward an
introverted instructor who would rather sit back and facilitate through other channels. An
introverted instructor’s focus is on thoughts and ideas (Capretz, 2003), indicating
guidance through self-discovery, peer learning, and activities that provoke thought and
consideration. Introverted instructors are comfortable with a silent classroom (Capretz,
2003) and may be inclined to let students guide themselves with unobtrusive assistance.
Background
Cattell (1943) and Eysenck (1964) first identified the introversion-extraversion
traits as being a consistent and dependable aspect of personality. Both researchers
developed personality tests that measured levels of extraversion. Cattell established the
16 Personality Factor questionnaire as being reliable and valid utilizing various methods.
Cattell’s findings suggested there were high correlations between self-reports and ratings.
Fashioned by Eysenck and Eysenck (1964), the Eysenck Personality Inventory’s (EPI)
focus was on two components of personality: extraversion/introversion and
neuroticism/stability. It comprised 57 yes–no items without replication of test questions.
The two dimensions of extraversion and stability were divided into four subsets: (a)
stable extraverts were those who were talkative, responsive, and carefree; (b) unstable
extraverts described individuals who were high-strung, impulsive, and impatient; (c)
stable introverts displayed passive, even-tempered, and dependable characteristics; and
6
(d) unstable introverts could be moody, anxious, and inflexible individuals (Eysenck,
1968).
It has been established that both the trait of extraversion (Costa & McCrae, 1994)
and learning style (Richardson, 2011) remain constant over long periods of time,
indicating an inherent preference for type and degree of human interaction. Terracciano,
Costa, and McCrae (2006) substantiated findings that personality traits are primarily
consistent after the age of 30 and plateau about age 50. Variables of gender, ethnicity,
and education had no influence on personality stability (Terracciano, McCrae, and Costa,
2010). According to the National Center for Education ( as cited in the American
Association of Community Colleges, 2013), 45% of community college faculty are over
49 years of age, with 37% between the ages of 40 and 49, indicating an assurance in
personality stability of the instructors referred to in this study.
Additionally, it has been suggested that instructors teach in the way they
themselves learn best (Stitt-Gohdes, 2003). Therefore, those instructors possessing an
ample amount of extraversion may prefer lively conversations, different points of view
and group work in their classroom (Shah and Meisenberg, 2012) while instructors low in
the extraversion trait may assign reading material and give written assignments
frequently (Offir, Bezalel, and Barth, 2007).
This premise does not mean that teachers should avoid adopting various strategies
in accommodating their students, but that modifications can be minimalized if students
are predetermined to respond to a certain instructor personality type. Champagne (1991)
stated that learning styles could change and adapt over time, and concessions should be
7
made accordingly. However, those concessions might involve a different instructor with
an established method of delivering information. These methods could involve
PowerPoint presentations, peer presentations, group work, or assigned readings. If
students’ learning styles change, then choice of instructor, according to degree of
extraversion, may also deviate.
Community college students comprise people from many facets of life. Many are
parents (married or single) with financial and family responsibilities. Some are first
generation college students unfamiliar with collegiate academia and lacking in guidance
from parents and relatives who never attended college. Unlike the traditional college
student, many of these individuals view themselves as employees who choose to register
for college (20%), who select a part-time schedule (44%), and who live with their parents
(61%; Mullin, 2011). According to Mullin (2012), the student population in community
colleges has become younger, with a growing number registering for courses before
graduating from high school. This shift is due to the fact that secondary schools are
providing opportunities for college credit. In addition, the female population has
increased over the last 30 years in community colleges, standing at 58% in 2008, while
male enrollment has remained steady with only a slight increase in recent years (Mullin,
2012).
The format in which community college education takes place provides
opportunity, accessibility, and affordability. Baum, Little, and Payea (2011) described
the conveniences of community colleges by identifying the lower admission
8
requirements, geographical proximity, and flexibility in scheduling compared to 4-year
universities. Mullin (2012) stated that 84% of community college students work, with
60% of those students employed more than 20 hours per week, making it more difficult to
earn a degree. Community colleges service slightly less than half of all minority college
students, with 58% of all African American undergraduates and 66% of all Hispanic
undergraduates enrolled in community colleges (Mullin, 2012). As a result, community
college students encountered more risk factors than students from other institutions of
higher learning. Nevertheless, 71% of the U.S. population was in favor of an individual
beginning an educational pursuit at a community college (Associated Press, 2010).
There have been few studies conducted on achievement level with part-time
community college students (Williams & Kane, 2010). McKenzie and Gow (2004)
established that learning strategies predicted grades twice as often in older adult
community college students in relation to the customary-age college student.
Furthermore, data indicated that 61% of all community college students take at least one
remedial course, while 25% take two or more (Goldrick-Rab, 2010), implying the need to
meet students at a lower academic level than was originally designed for a course and
also indicating a slow progression toward degree or certificate completion. Consequently,
diversion in both student population and institutional goals presented a variety of
impediments to the community college students’ endeavors.
Community college instructors have unique work environments and challenges
that influence the way they teach. They cater to an eclectic community of unemployed,
underemployed, and displaced workers seeking to make a new start. They provide
9
instruction to the young as well as the old, the middle class and the underprivileged, the
single parent, and the recent high school graduate. They may teach students seeking to
continue their education at a 4-year university or someone who just wants to brush up on
a specific area of interest. Regardless of the student, community college instructors must
enter the classroom accustomed to the complexity of the student body and ready to adjust
instruction accordingly. Dissimilar to 4-year universities, where the instructor is required
to present curriculum and the students are expected to acquire it, community college
instructors must take into consideration the complex needs of their students, including
their social and psychological backgrounds. However, while enrollment and challenges
increase, salaries are shrinking for the community college instructor (Alexander,
Karvonen, Ulrich, Davis, & Wade, 2012). Delayed retirements and slow faculty turnover
rates may be an explanation for this trend. In addition, higher paying sectors and heavier
course loads may promote the lack of qualified instructors in the community college
arena.
Unlike other higher learning institutions, a community college instructor’s focus
is on teaching, as opposed to research and publication demands (Grubb, 1999). Grubb
(1999) asserted that many instructors in a community college felt isolated due to the
focus on teaching and the absence of academic camaraderie among their colleagues, who
at a 4-year university may serve as mentors or give support and advice. According to
Goldrick-Rab (2010), community college administrators tended to overlook effective
teaching strategies in favor of content knowledge. The instructors might choose to
develop teaching methodologies by trial and error or to mimic their own learning
10
experiences by teaching in the way they themselves were taught. Goldrick-Rab (2010)
described a typical community college instructor as having a master’s degree in his or her
subject area and working for several community colleges as an adjunct professor. The
approximate percentage of part-time faculty nationwide has increased from 20% in 1970
to 49% in 2007 (Ehrenberg, 2012).
Community college instructors, more so than 4-year college instructors, must
attend to the needs of various students by providing an appreciation and excitement for
learning that might not be innately ingrained. They must furnish avenues for students to
acquire the subject matter, recognize progress, and apply it in real world scenarios.
According to Fugate and Amey (2000), all instructors should acquire those competencies,
but for community college instructors, it is especially important to have worked in the
field in which they were now teaching.
Statement of the Problem
Many studies have recognized the importance of instructor/student cohesion
(Frisby & Martin, 2010; Sierra, 2010). Personality constructs, learning styles, and their
relationships have been examined extensively, and yet the investigation into instructor
extraversion level and student learning style has no finite conclusions. Community
college instructors and students are a unique and definable group in academic society.
Community colleges have minimal admission standards that contribute to a low
completion rate (Mullin, 2012). In many cases, these students’ investment in education
can be ambivalent due to the complications of being minorities, parents, and full- or part-
11
time workers (Mullin, 2012). Consequently, community college instructors are
encouraged to expend a considerable amount of energy providing necessary instruction
that accommodates students who are not prepared or have little time for the rigors of
higher academia. By matching student learning style to instructor degree of extraversion,
some of these barriers could be lessened.
However, community college instructors have their own set of frustrations. Many
community colleges employ adjunct professors, offering low salaries and large class sizes
(Modern Language Association Committee on Community Colleges, 2006). As a result,
instructors are overwhelmed at the prospect of meeting the needs of all students and may
become disillusioned with the students’ inability to grasp concepts and ideas (Modern
Language Association Committee on Community Colleges, 2006). Alleviating
problematic conditions should consist of an attempt to create teaching environments that
are conducive to both instructors and students by attending to inborn predispositions of
teaching and learning. Undoubtedly, this affiliation of instructor extraversion and student
learning style could not be accomplished in every instance. A limited selection is
foreseeable in some cases due to student last minute enrollment, retiring faculty, and area
of expertise. However, academic institutions can delegate faculty, who have tenure or are
retained from year to year, to classes that are grouped according to the instructor’s
propensity to connect with a particular type of learner.
Purpose of the Study
I analyzed the relationship between the instructor’s level of extraversion and the
students’ learning styles of auditory, visual, and kinesthetic modalities. I compared the
12
extraversion trait in community college instructors with their students’ dominant style of
learning (auditory, visual, or kinesthetic) to determine any correlational significance. I
reviewed mean differences in age, race/ethnicity, and gender for noteworthy preferences
for teacher degree of extraversion or student learning style. The intent was to provide
academic institutions with methods of grouping students according to the way in which
they learn and to provide instructors whose inherent extraversion trait enhances the
learning experience, thereby eliminating obstacles to learning. The purpose of this study
was to heighten awareness and attend to natural inclinations toward gaining knowledge.
Research Hypotheses
In this study, I sought to determine if a correlation existed between the processes
by which an individual learns (auditory, visual, or kinesthetic) and the degree of
extraversion permeated in the instructor. The research questions are as follows: Is there a
relationship between teacher extraversion and a student’s dominant learning style? Is
there a relationship between teacher extraversion and a student’s visual learning style? Is
there a relationship between teacher extraversion and a student’s auditory learning style?
Is there a relationship between teacher extraversion and a student’s kinesthetic learning
style? I describe, in Chapter 3, the research hypotheses and the methodology used to
ascertain the answers in detail. The variable of teacher extraversion would be measured
using the extraversion portion of the Big Five Inventory (John, Donahue, & Kentle,
1991), while the three learning styles of visual, auditory and kinesthetic modalities were
measured utilizing the Barsch Learning Style Inventory (Barsch & Creson,1980). The
hypotheses are stated as follows:
13
1. H0: There is no relationship between teacher extraversion and student’s
dominant learning style.
H1: There is a relationship between teacher extraversion and student’s
2. H0: There is no relationship between teacher extraversion and visual learning
style scores.
H1: There is a relationship between teacher extraversion and visual learning
style scores.
3. H0: There is no relationship between teacher extraversion and auditory
learning style scores.
H1: There is a relationship between teacher extraversion and auditory learning
style scores.
4. H0: There is no relationship between teacher extraversion and kinesthetic
H1: There is a relationship between teacher extraversion and kinesthetic
Definitions
Theoretical Constructs
The term learning style is used to describe various constructs of learning or
instructional preferences. According to Pritchard (2009), learning style is an individual’s
favored approach to thinking and processing information. It entails inherent or learned
14
strategies and habits. It conceptualized individual choice as well as practices and
procedures. The many modules of learning styles included, but were not limited to, (a)
sensors: those types tended to be detailed-oriented and practical, concentrating on facts
and procedures; (b) intuitors: imaginative and meaning- or concept-oriented; (c) thinkers:
very logical and rule-oriented individuals; (d) feelers: those who made decisions on a
more personal basis, and (e) judgers: people who often followed agendas, seeking
closure. Moreover, included in the list of learning styles were reflectors, perceivers,
theorists, activists, and pragmatists.
In this research, I considered the three learning modalities of auditory (those who
are susceptible to the spoken word), visual (those identifying with graphic cues), and
kinesthetic/tactile (those individuals who desire motion) learners (Dunn, Griggs, Olson,
Beasley, & Gorman, 1995). As detailed in Chapter 2, this research considered
personality theories described by Jung (1959) and Eysenck (1964) and the pedagogical
practices of instructors possessing or lacking extraverted personality characteristics. Sun
(2012) described a mismatch of student learning style and teaching presentation as
contributing to problematic conditions of anxiety and negative attitudes among students
and instructors alike.
Wilt and Revelle (2008) suggested one objective should be an examination into
extraversion and student academic functioning. According to Fang (2012), the
incompatibility between instruction styles and learning styles is evident and therefore
deserves attention. Data will be collected in a community college located in the
southwestern part of the United States. These three constructs of auditory, visual and
15
kinesthetic learning styles have met established, reliable, and valid psychometric
standards, and they are also easily understood by the general public (Dunn, Beaudry, &
Klavas, 2002).
Definition of Terms
Auditory learning style: Includes learners who have good listening skills. Having
a respectable auditory memory, they benefit from audio tapes, interviewing techniques,
lectures, and discussions (Dunn & Honigsfeld, 2009).
Extraversion: One of the Big Five personality traits. The true ultimate extraverted
personality is uninhibited, gregarious, and fun loving. This type of personality loves
crowds and group activities and smiles a lot. Extraverts are spontaneous and optimistic
and like to entertain. They easily express their emotions and are confident and popular
(Dunn & Honigsfeld, 2009).
Kinesthetic/tactile learning style: Includes people who learn by doing. They like
to manipulate objects and enjoy physical activities. These types of students may find it
hard to sit still and need frequent breaks from the classroom (Dunn & Honigsfeld, 2009).
Visual learning style: Includes learners who prefer to learn through seeing. They
have visual recall and prefer information in the form of graphs, maps, displays, and
diagrams (Dunn & Honigsfeld, 2009).
Significance
Individuals choose what they learn (Fraser & Greenhalgh, 2001). Champagne
(1991) asserted that the attention given to information and the value the students placed
on that information was essential in the learning process. If students could digest
16
knowledge efficiently and with minimum effort, instructors could move through material
more rapidly, therefore covering more material; students would gain more knowledge,
skill, and interest; course enrollment would increase; and classes would flow more
smoothly than before. In many cases, people attend to that which is understood and
absorbed readily, and that which is understood thoroughly can be applied effortlessly and
with much success. Accomplishments impact the perception of what the mind, body, and
soul can do, affecting the lives of one or of many (Zepke and Leach, 2010).
Everyone has a learning style (Dunn et al., 2002). Dependent on the combination
of learning modalities—presentation style preferences, instructor characteristics, or
classroom environments—an individual will adjust accordingly to the best of his or her
ability. It is convenient to have cooperation and cohesion when trying to adjust. Stress
levels are reduced, a comfort level is established, and learning becomes potentially
promising.
For community college students who already have unique obstacles to overcome,
the small but significant gesture of deliberately placing them in an environment
conducive to their learning style could enhance their educational experience. Erton
(2010) contended that teachers should cultivate their teaching styles to purposefully meet
the needs of learners. That suggestion, while valid, is incomplete by not proposing an
adjustment to student groupings that complements an instructor’s intrinsic personality
type.
While research on instructor personality type and student achievement has not
reached any consensus on an all-inclusive model, it has identified potential projects for
17
examination. Sun (2012) proposed an investigation into the incompatibility of
student/teacher relationships; Salehi (2010) suggested that future studies should
concentrate on personality factors of students and teachers; while Harris and Sass (2010)
asserted, “Teachers significantly influence student achievement, the variation in teacher
productivity is still largely unexplained by commonly measured characteristics” (p. 1). I
attempted to analyze a small component of teacher/student compatibility with the
intention of contributing to the literature of pedagogical practices.
Nature of the Study
A quantitative approach to this study includes gathering scaled data from students
at a community college in the southwestern United States. A cross sectional design of
instructor’s degree of extraversion with the variables of an auditory, visual, or kinesthetic
learning style will be examined for any significant correlations. According to Cohen,
Cohen, West, and Aiken (2013), a cross sectional study may be used to define a fraction
of the population using multiple regression. This study is not concerned with a cause and
effect relationship, nor can it describe variations over time. However, the quantitative
approach is appropriate for testing hypotheses in this research involving the correlation of
independent variables. In addition, demographic information of race/ethnicity, gender,
and age are taken into consideration as covariates.
Assumptions and Limitations
An assumption in this study consists of the participants’ willingness to take part in
completing the inventories, knowing there is no compensation or penalty involved. I
expected that participants would answer truthfully and to the best of their capability,
18
realizing that recall may not be easily forthcoming at the moment the inventory is
completed, leaving the participants with an “I forgot about that instructor” and a
hindsight disposition. Consequently, memory difficulties could result in inaccurate and
biased responses. However, it is assumed that the instruments involved in this study are
appropriate measures of the constructs to be examined and can be applied to a
comparable population.
As the researcher, I recognize the omission of factors that could influence
findings. The study is administered in the southwest region of the United States and may
not be applicable to other regions or nationalities. Additionally, it is not this study’s
purpose to defend a three-sizes-fits-all approach to teaching, knowing that different
blends of learning styles can complicate meeting the needs of every student. A causal
relationship is not assumed between any of the variables under investigation, and
therefore, results can only indicate significant associations between student learning
styles and instructor level of extraversion. Plausible reasons for connections (if any) will
be offered. While the study undertaken will not result in definitive answers, it is designed
to encourage speculation about academic practices and its results.
Summary
The origin of this research began with observations of interactions between
various teachers and students in numerous classes over a number of years. The perception
of various teaching techniques intertwined with instructor personality sparked an interest
in differing responses from students and their implications. Students have various
strengths and weaknesses, motivational levels, cultural influences, ambitions, and
19
interests. Likewise, instructors have varying levels of these same categories. Felder and
Brent (2005) designated teaching styles as a conduit to the acceptance of education and
all that it entailed. They reported, “How much a given student learns in a class is
governed in part by that student’s native ability and prior preparation but also by the
compatibility of the student’s attributes as a learner and the instructor’s teaching style”
(p. 57). While some instructors focus on principles or applications, some opt for
understanding over memory (Bain, 2011). Other instructors lecture in lieu of
demonstrations. It is feasible that these inclinations are derived from personality
constructs that encourage a particular approach to methods of presentation.
There are instances of definite mismatches between student and instructor,
whether it is from a bad first impression, a disagreement, or an incompatibility of another
sort. These personality obstacles are sometimes inevitable and can prevent effective
teaching practices from occurring and inhibit learning. It is also possible that the
instructor/learner relationship has no bearing on learning at all, with each seeing the other
as strictly a learner or a teacher. However, when at all possible, this interaction should be
conducive to the giving and receiving of information, the guidance and acceptance of
knowledge, and the encouragement and motivation to create and imagine.
Instructor/learner communication must rely on both parties’ ability to excuse minor
irritations and incongruences, and yet, optimizing the match between personality and
learning components proves beneficial to all.
In Chapter 2, I addressed the history and discovery of the Big Five personality
traits, including the heritability, evolutionary, and biological components of the
20
extraversion trait. Learning style characteristics and their definitions are included in this
discussion in conjunction with implications for detecting individual modalities of
learning. The development of assessments applied in the research of personality and
learning styles is described, along with different models for teaching, learning, and
implications for future research.
In Chapter 3, I described the process by which this study would be conducted.
The purpose of the study, participant characteristics, and instruments applied are
highlighted in this section. The research design and approach are explained in detail, with
a description of the type of analysis selected. Administering and scoring procedures, as
well as ethical considerations, are discussed. Appendices of the inventories are attached.
In Chapter4, I will describe data collection procedures, and report significant findings of
the statistical results. In Chapter 5 I interpret findings and address conclusions and
recommendations.
21
Chapter 2: Literature Review
Introduction
An educator’s ability to connect with students on various levels is determined by
the attributes and detriments of both teacher and student. An ideal teachable moment is
when students grasp an idea, concept, or fact that entices them to ponder further, make
connections, and originate new ideas. Although the educator’s role in facilitating these
student epiphanies develops through training and skill, innate characteristics may
enhance or detract from the learning experience. This literature review is focused on the
personality trait of extraversion in community college instructors and its relationship to
the different learning style categories of visual, auditory, and kinesthetic (used
interchangeably with tactile) learners.
Community colleges serve about 30% of all students entering higher education,
yet only one in four students graduate from a community college (Chen, 2011). Cutting
the dropout rate by half would produce income of $30 billion for these individuals and
create additional revenue of $5.3 billion for the economy (Chen, 2011). In 2009,
approximately 400 community colleges had graduation rates less than 15% (Schneider &
Yin, 2012). Undoubtedly, increasing graduation rates among higher education students
would benefit an industrial society’s substantial demand for an educated, technical, and
skilled workforce. According to Chen (2011) and Schneider and Yin (2012), only a small
number of scholars have attempted to address the issue of community college students’
dropout rates.
22
According to Murray, Rushton, and Paunonen (1990), few researchers have
examined faculty characteristics that might contribute to engaging community college
students. A professor who predominantly lectures throughout a course may find student
disinterest in abundance. Students must see the immediate, as well as long term, benefits
to completing a higher education. Notwithstanding many other variables (Anders,
Frazier, & Shallcross, 2012), classes must be engaging enough to hold the students’
attention, influencing the belief that course enrollment is worthwhile, despite outside
obstacles that typically interfere with the progress of community college students. An
abundance of literature has suggested that students learn differently (Murray & Moore,
2012; Sadeghi, Kasim, Tan, & Abdullah, 2012). Understanding differences and attending
to them could be one of the factors that may increase student retention, achievement, and
ultimate success. The purpose of this study was to determine whether there is a
relationship between an instructor’s personality traits (specifically, the trait of
extraversion) and a student’s learning style. If so, recognition of established personality
dispositions among and between instructors may divulge instructing styles that attend to
auditory, visual, and kinesthetic learning styles.
An examination of the theoretical foundation of personality offered by Carl Jung
(1959, 1971a), including the review of Jungian theory of archetypes and the development
of the extraversion/introversion component, is included in this chapter, along with the
development of the Myers-Briggs Personality Profile Inventory (Myers, McCaulley, &
Most, 1985). A description of Eysenck’s (1975) contribution to a conceptual framework
is a crucial element in the examination of extraversion. Likewise, an investigation of the
23
five-factor personality theory (McCrae & John, 1992) with an emphasis on the
extraversion component is merited. In addition, this literature review will probe into the
genetic/biological research of extraversion and its ramifications.
Instructional models and teacher presentation styles are duly noted components of
this literature review, as well as the need to revisit contemporary methods of instruction.
Although research on instructor extraversion and student outcomes is limited (Wilt &
Revelle, 2008), the research on teacher personality and student effects is referenced,
highlighting an assortment of techniques and models (Jaskyte, Taylor, & Smariga, 2009;
Neff, Wang, Abbott, & Walker, 2005; Patterson & Purkey, 1993; Simpson, Gangestad, &
Biek, 1993).
Turning the focus toward learning styles, the consideration of Gardner’s theory of
multiple intelligences (Gardner & Hatch, 1987) is warranted, along with the review of
biological associations to styles of learning. The learning theories of Dunn and Dunn
(Dunn, Dunn, & Price, 1985) and the VAK model, which stands for visual, audio, and
kinesthetic theories of learning, are also included in this chapter. The VARK model of
Fleming and Baume (2006) is an extension of the VAK, adding to its model a
reading/writing component. Assessed are deliberations on the individual aspects of each
learning style and the implications of corresponding teaching methods, accompanied by
the implications of prior research findings involving community college instructors,
students, and pedagogical procedures. Moreover, Kolb’s (2005) experiential learning
theory is taken into account as an added dimension of the learning schema. Finally,
included in this chapter is an inspection of the implications and limitations of
24
past research, present research, and this literature review, with a summation of all entities
involved.
The search engines used for this literature review consisted of the Walden
University Library Portal, Ebsco Host, and Google Scholar. Terms used for those search
engines were extraversion, introversion, learning styles, visual, kinesthetic, auditory
personality traits, Carl Jung archetypes, Myers-Briggs personality traits, Eysenck,
teaching styles, teacher personality, university/community college students,
university/community college instructors, history of extraversion, extraversion and
instructors/teachers, genetic components of extraversion, genetic components of learning
styles, the Big Five personality theory, instructional models/university, instructional
models/community college, and student/teacher personality mismatches. Materials were
gathered from peer reviewed journal articles, books, trusted websites, and state and
federal statistics, with most sources dated within the last 20 years. Databases were
Academic Search Complete, Education Research Complete, ERIC, PsycARTICLES,
PsycBOOKS, PsycCRITIQUES, PsycEXTRA, PsycINFO, Research Starters, and the
Education Teacher Reference Center.
Instructional Models
A long-standing contention is that many teachers teach the way in which they best
learn (Hammerness et al., 2005; Wirz, 2004). Shah and Meisenberg (2012) reported on
the reception of various teaching modalities among first-year medical students and
instructors. Participants included 30 faculty members and 327 students. They were asked
questions about handouts, lectures, media-based learning, textbooks, problem-
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based learning, team-based learning, and practicums. Students scored highest on mediabased learning instruction, trailed by simulation, handouts, and practicums. Students gave
the lowest score to textbooks, problem-based learning, and team-based learning, while
instructors gave the highest scores to lectures, followed by practicums and textbooks, and
the lowest scores to team-based learning. Lectures, viewed as unpopular by students in a
physical classroom environment, were valued more than other methods when provided
through computer technology. Recorded lectures afforded students the opportunity to
study any time and to repeat important parts, as well as to speed through the mundane
parts of a lecture. Overwhelmingly, extraverts (who were not lovers of reading) did report
enjoying small group activities and problem-based and team-based learning
environments.
Polk (2006) proposed that it was the student who could determine clarity in
information delivered and was therefore the deciding entity in the degree of
successfulness of the provided delivery. “When students cannot learn the way we teach
them, we must teach them the way they learn” (Dunn, 1990, p. 15). A pedagogical theory
that has been given much attention in recent years is an eclectic method to instruction
(Nurmi, Viljaranta, Tolvanen, & Aunola, 2012). Teachers adjust their instruction
according to learners’ educational performance. The undeniable awareness of
individuality beckons this approach with vigor and persistency, reinforcing the
uniqueness of mankind. Mankind is mindful of its differences and attempts to appease
them.
26
The numerous models for instruction consist of various and cumulative degrees of
cooperative learning, direct instruction, self-directed learning, visual stimuli (Power
Points, charts, maps, graphs, and computer-simulated scenarios), guest or expert
speakers, hands-on investigations, role playing, writing, audience response systems
(clickers that promote interactive engagement), conversing, reading, internships,
residencies, and interactive conferencing. Of course, instruction must always maintain a
purpose. Goals and objectives containing the three elements of planning the instruction,
delivering the instruction, and finally assessing the instruction delivered are essential
components. The focus of a portion of this chapter will be on instructional delivery in a
conventional classroom setting and how it may differ according to the degree of
extraversion. The instructional objective is for students to memorize, analyze, problem
solve, think critically, reason, apply, and interpret. The instructor, using skill, expertise,
and personality characteristics, must deliver instruction in a meaningful way.
Jung and Extraversion
Jung (1959, 1971a) developed the concepts of introversion and extraversion as
elements of deep-rooted subconscious patterns of reactions to the world. Extraverts were
seen as those who react to outward forces and rely on others as an energy source, while
introverts choose solitude, seclusion, and reflection to regain their energy. The extravert’s
attention is geared toward objects. “If a man thinks, feels, acts and actually lives in a way
that is directly correlated with the objective conditions and their demands, he is
extraverted” (Jung, 1959, p. 333). The conscious mind of the extravert was prone to an
27
immediate environment, responding both to people and items. The extravert’s value for
an object was forever increasing, relying on positive connections to fuel satisfaction with
life (Jung, 1959, 1971a).
According to Jung (1959), the introvert had an aloof attitude toward the object or
person and a need for space and privacy. Although the introvert was aware of external
forces, the choice of responding to subjective determinants was evident. Orientation arose
from perception and cognition, not necessarily concrete reality.
Jung (1959, 1971b) considered personality types as dimensions of the trait of
extraversion. Those dimensions were thinking, feeling, sensing, and intuiting functions
(Jung, 1959). Jung (1959) further stated that a degree of extraversion (or lack thereof)
dictated the results of a combination of those four functions. Thinking was the act of
perceiving cause and effect relationships and the way (distant in regard to introversion or
forthright in regard to extraversion) in which questioning was pursued. The feeling
element attended to the characteristics of warmth and intimacy and how the degree of
extraversion dictated those outward tendencies (Jung, 1959). The sensing function was
the extent a person relied on present and immediate physical or biological details (Jung,
1959). Digesting circumstances as they seemed to be, no more, no less, implied an
extraverted personality type. The intuitiveness aspect described features of leaning
toward hunches and impatience with concrete details, which might indicate a lack of
extraversion tendencies. Jung (1959) perceived thinking and feeling factors as rational
types, while sensing and intuitive factors were seen as irrational. A discussion of the
pairing of each type with the extraverted or introverted personality trait follows.
28
According to Jung (1959), normalcy for the extravert depended on the ability to
acclimate to the present, while dispatching the unconscious (interchangeably used with
the subjective mind) into a submissive ineffective state. Even though the extravert’s
thinking was based on concrete objects and concepts, idealistic thinking could also arise
in the extravert if extracted from external sources. Thinking was positive and productive,
leading to facts and truths based on empirical evidence. For the introverted thinker,
intensity was preferred over extensity (Jung, 1959). Jung stated the complexity of thought
might oftentimes produce contradictory and inconsistent patterns in introverted thinkers,
allowing for the entanglement of conceptions. Ideas were formulated inwardly as
opposed to outwardly, and displays of indifference, if not intolerable attitudes, were
geared toward people and objects. The introvert’s thoughts might appear arrogant and
egotistical to some due to a stubborn headstrong demeanor that insisted what was
inwardly clear and coherent was accordingly comprehensible to everyone else.
The feeling component of an extravert was always in accord with society’s objective
standards. A sentiment might be acknowledged by the extravert just because it was
politically correct to do so. Jung (1959) described how a famous painting would be
labeled as beautiful to the extravert, because it was created by a famous artist or as not to
offend the host exhibiting the picture. The extravert’s aim was to correspond to objects
that enhance social stature or credibility among others. The attention sought from the
object became what was most valued. Contrastingly, the introvert’s inclination was to
devalue the object in preference for subjective thought. Their aim was to scrutinize the
object in conjunction with internal truths, interpreting essential elements that might be
29
negative judgments. The feeling patterns of the introvert were not dependent on approval
by or persuasion of others, but rather introverted feeling rested with the perception of
oneself. Jung portrayed most introverted feeling types as female. He stated they were
quiet, difficult to understand, and possessed a quality of sadness. True motives for their
feelings were usually hidden, especially when the object was overwhelming.
Jung (1959) contended that the extraversion sensation personality typology
experienced true enjoyment. Tangible involvements with concrete objects were at the
crux of that personality type. Sensing actual life circumstances to its fullest, the extravert
sensation type loved reality with little room for reflection. Living in the moment was of
great importance, therefore that personality type was usually jovial and excellent
company at social events. Sensing life deeply, the sensing extravert desired strong
ambiences whether pleasurable or not. The introverted attitude toward sensations was one
of subjective dominance. It was a self-interpretation of an object, which in reality might
be of little use to the outside world but had meaning and significance for the individual.
According to Jung (1959), intuition was an unconscious process that was difficult
to grasp. It was an expectancy or prediction of the foreseeable future dependent on
concrete objects for the extravert and inner stirrings for the introvert. Jung proposed that
the characteristic of intuition attempted to capture a wide range of possibilities, revealing
itself through tangible factors in the case of extraverts or physical symptoms and inert
yearnings in the case of introverts. According to Jung, the extraverted intuitive type
would gravitate toward novelty experiences. Unchanging circumstances were irritants
and the urgency of change apparent. Jung suggested many people who fell into that
30
category chose professions of entrepreneurs, politicians, and stockbrokers; they had the
ability to spot potential in people and to champion rights for minority groups. Introverted
intuitive types were found in artists and the like. They had the propensity to let the mind
wander into whimsical or grotesque images. The mind, being limitless, speculated upon
the unimaginable.
Jung (1959) viewed the unconscious as a compensation device that provided an
equalizer to the conscious mind, but was a recessive factor with little surfacing to the
conscious. However, an exaggerated version of the extraverted psychological type was
dangerous to the subjective mind in that it suppressed natural tendencies, intentions,
desires, and needs—elements with a history of acknowledgement. Jung stated the less
those tendencies were recognized by the extravert, the more primitive and infantile they
became, until they were reduced to primordial instincts. Those instincts could only be
eliminated through a slow transformation of genetic makeup. At that point, the
unconscious went beyond childish selfishness to a vicious and brutal place where
extraversion was at its peak and the subjective mind was manifested through a nervous
breakdown.
Eysenck and Extraversion
Jung (1959) did not see extraversion as dimensions on a continuum, but rather he
perceived extraverts and introverts as separate types of people. It was not until Eysenck
(1964) examined Jung’s proposals that extraversion was seen in dimensions of stronger to
weaker degrees of functioning. In the 1940s and 1950s, it was Eysenck who performed
studies on the importance of extraversion as a personality trait. Pioneering the
31
investigation of the core features of extraversion, Eysenck (1975) described individuals
with a high degree of extraversion as impulsive and social. In addition, they were
assertive enthusiasts who gravitated toward change, warmth, and gregariousness.
Eysenck (1975) described those low on the trait of extraversion (introverts) as
having reflective behavior: reserved, quiet, and shy. They were those silent types who
seemed to be taking in conversations rather than contributing to them. Eysenck
hypothesized that extraverted people had a strong sense of inhibition. The extravert’s
brain, because it was accustomed to and gravitated toward outward stimuli, could absorb
devastating circumstances with less shock, sheltering itself from the full memory of a
catastrophe and enabling the brain psychologically to recover rapidly. On the other hand,
an introvert’s brain, possessing weak inhibition and unaccustomed to embracing outward
stimuli, might be unable to shield itself psychologically from a horrific event.
The brain’s protection mechanism did not come to the rescue fast enough,
exposing introverts to posttraumatic symptoms. Eysenck (1964) proposed that extraverts
committed most violent criminal acts. People with that personality trait were able
mentally to dismiss a violent act and emotionally to recover quickly to repeat more
violent acts. Contrastingly, extraverts required less positive stimuli to produce an effect
(Wilt & Revelle, 2008).
Wundt and Judd (as cited in Matthews, Warm, Reinerman, Langheim, & Saxby,
2010) maintained that extraverts should perform better on tasks requiring speed and
accuracy, because arousal level would peak, which was what was sought. That also
32
implied that the use of stimulants, social interaction, and sexual activity was higher and
more prevalent among extraverts.
Gray’s (1970) development of an alternative theory to extraversion, the
reinforcement sensitivity theory (RST), involved animal data and was much harder to
generalize than Eysenck’s. However, his theory did make a forthright prediction that
extraverts were more conducive to rewarding stimuli and therefore produced a more
positive effect in learning endeavors when offered rewards.
The Evolutionary Basis for Extraversion
Psychological mechanisms involve evolutionary processes, and extraversion is no
different. Buss (1995) suggested that the evolution of extraversion arose from communal
tasks demanded from the social environment. Those tasks could be summarized through
behavioral approach and behavioral avoidance structures. Wilt and Revelle (2008)
postulated that it was the behavioral approach system that was associated with the
extraversion continuum. However, Eysenck (1975) warned that although there was solid
evidence to suggest the relevance of genetic factors, relegating gene dominance in
preference for introversion or extraversion was a mistake. There were probably instances
where the survival of society was dependent on spontaneous and social attributes in
certain situations and reclusive or preplanned qualities in others. Nettle (2004) stated that
although in the evolution of extraversion, an extraverted individual might have more
mates and procreation opportunities, their risky behavior could also cause them to die
33
earlier, thus discontinuing the passing on of their gene pool.
The Biological Basis of Extraversion
The suggestion that extraversion has biological factors implies that these factors
should appear in an individual’s early development. Rothbart, Ahadi, and Evans (2000)
found that to be the case. Studying temperament, a positive affect that coincided with the
degree of extraversion trait had been found in infants as young as 3 months old.
Temperament is related to variations in self-control and reactivity, and it was discovered
that those characteristics overlapped with both Eysenck’s (1975) and Gray’s (1970)
findings on impulsivity and reinforcement sensitivity.
In addition, support for a genetic component of extraversion can be found in
research conducted on animals. Luo, Kranzler, Zuo, Wang, and Gelernter (2007)
determined genes identified with extraversion as ADH4. Through MRI testing, it was
discovered that extraversion was linked to the amount of gray matter in the left amygdala
and that lower amounts of gray matter could predict depression. Similarly, extraversion
was connected to the thickness of the orbitofrontal lope, and research findings had
concluded that low thickness in the prefrontal cortex implied impulsiveness and
uninhibited behavior (Omura, Constable, & Canli, 2005).
Many had postulated that the trait of extraversion had several determinants and
that independent variables might skew results. In addition, Eaves and Eysenck (1975)
asserted that the two major components of extraversion were impulsivity and sociability,
and that those characteristics could be linked to environmental and genetic factors. It had
been asserted that differences in extraversion behavior could be attributed to numerous
34
variations in cortical arousal, and those individuals with fewer extraversion tendencies
were aroused to a greater extent than those with more extraversion tendencies from the
same stimuli (Schaefer, Heinze, & Rotte, 2012). That research implied that introverts had
a lower threshold for excitement than extraverts, and that the extraverted individuals
might be inclined to seek out stimulating events. Other research had linked the
personality dimension of extraversion to regions in the prefrontal brain (DeYoung et al.,
2010), as well as the amygdala and the ventral striatum.
Results from a study conducted by Beukeboom, Tanis, and Vermeulen (2012)
suggested extraverts were linguistically abstract, whereas introverts were more concrete
in their language delivery, and therefore, had a higher degree of credibility when
speaking. Verification of that notion could be observed in social situations where an
extraverted personality type might dominate conversations, but because introverts spoke
so sparingly, when they did speak, everybody listened. Its most common label was
extraversion, and its proximate basis was thought to include deviation in dopaminefacilitated reward circuits in the brain (Depue & Collins, 1999). Introverts innately had a
tendency to compensate for high arousal stimuli by withdrawing. Contrastingly,
extraverts welcomed arousing stimuli, because it took more to excite them. Those who
felt the need to be aroused might possess a higher degree of neuroticism than those who
were stable (introverts) and had lower thresholds in the intuitive brain (Depue & Collins,
1999).
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The Heritability of Extraversion
According to Nettle (2006), it was uncommon for a single gene to vary in its
influence over an inheritable trait; however, those traits affected by several genes were
more prone to producing mutations. In fact, the likelihood of mutations was in direct
proportion to the number of genes involved. The genes, ADH4 (Luo, Kranzler, Zuo,
Wang, & Gelernter, 2007), were identified as polymorphic contributors to the trait of
extraversion. Several ADH4 markers contributed to variation in degrees of extraversion,
and therefore, various phenotypes and genotypes of extraversion were inevitable.
Positive and negative emotions, social ability, and reactivity are dimensions
included in all personality constructs. Considering Eysenck’s (1975) proposal that
extraversion was made up of the two components of sociability and impulsivity, there
was evidence to suggest that sociability, and therefore an element of extraversion, was
inherited (Plomin, 1974). Conversely, the evidence on the inheritability of impulsivity
was mixed (Buss & Plomin, 1975); nevertheless those two factors were highly correlated
to each other (Plomin, 1976). Nettle (2006) contended the trait of extraversion was
strongly connected to the number of sexual mates, which could increase physical prowess
and sustainability. Those who scored high on the extraversion trait were also prone to
terminating relationships in preference for other sexual partners, resulting in homes that
were step-parented, a known risk for children (Nettle, 2006). Extraverts were more
physically active and gravitated toward explorations of their environment, cultivating
social behavior and securing higher quality mates both physically and intellectually. For
36
that reason, more communal support was given to extraverted individuals than to
introverted individuals, providing an assortment of engaging activities to satisfy their
sensation-seeking tendencies. Extraverts were risk takers and had a higher rate of
hospitalization due to accidents or illnesses than those who were not (Nettle, 2006). In
addition, extraverts had higher probabilities of migration, criminal and antisocial
behavior, and arrests records (Nettle, 2006).
Myers-Briggs Assessment
The Myers-Briggs Personality Profile scores personality based on four attributes:
a preference for outgoingness (extraversion) or seclusion (introversion); whether a
situation is assessed based primarily on external (sensing) or internal (intuitive) cues;
whether an individual is more prone to make decisions using logic (thinking) or emotions
(feeling); and whether an individual is susceptible to judging or perceiving (Sears &
Kennedy, 1997). The test was originally designed during World War II to help women
self-assess before entering the workforce for the first time while their husbands or male
relatives were away fighting for their country. It is now used in colleges and career
centers, as well as by psychologists to help their patients.
Perception implicates all the ways of becoming cognizant of the environment:
people, circumstances, or ideas. Judgment encompasses the various ways of coming to
deductions about what has been perceived. If individuals differ systematically in what
37
they observe and in how they reach decisions, then it is realistic for them to differ in their
securities, interests, responses, principles, incentives, and abilities.
In developing the instrument of the Myers-Briggs Type Indicator (MBTI; MyersBriggs, 1962), the aim of Briggs Myers, and her mother, Briggs, was to enlighten and
make accessible types of that personality theory to average individuals and groups
(Myers et al., 1985). They addressed the two related aims in the development and
application of the MBTI instrument, which were the documentation of rudimentary
preferences of each of the four dichotomies specified or imbedded in Jung’s (1959)
theory, and the identification and explanation of the 16 distinctive personality types that
resulted from the interactions among the preferences.
The MBTI categorizes people into four personality types: extraversion or
introversion, sense or intuition, thinking or feeling, and judging or perceiving (MyersBriggs, 1962). It is a multiple-choice test that produces a personality profile with a
combination of four paired facets of personality. Its aim is to simplify Jung’s theory of
psychological archetypes into meaningful applicable principles of personality types. As
previously stated, this chapter will concentrate on the extraversion/introversion
components.
Dimensions of Extraversion
The Big Five Personality Theory
A starting point into the history of the Big Five personality traits is at societal
language. Klages (1926), Baumgartner (1933), and Allport and Odbert (1936) all relied
on the natural language in defining personality characteristics. Allport and Odbert (1936)
38
set out to identify all the words in the English dictionary connected to human behavior.
Their list consisted of 18,000 terms, represented an extensive yet all-inclusive set of
words used by the English-speaking population, and reflected societal perception of
importance in describing human actions, thought, and temperament. The combining and
organizing of those words resulted in four major categories, comprised of (a) personality
traits, such as sociable, fearful, or aggressive; (b) temporary states, such as rejoicing,
elated, or afraid; (c) personal conduct, such as excellent, irritating, or average; and (d)
physical characteristics, talents, and abilities—miscellaneous terms not appropriate for
the other categories.
Cattell (1943) condensed Allport and Odbert’s (1936) list to 4,500 trait terms
when he began his work on personality groupings. Through factor analyses, Cattell
documented 12 personality factors common among English-speaking Homo sapiens.
Those factors eventually became part of the 16 Personality Factor questionnaire (Cattell,
1943). Cattell contended the reliability and validity across various methods, such as selfreports and evaluations by others, had high correlational findings. Fiske (1949) replicated
but was unable to substantiate Cattell’s findings, detecting only five factors with
recurring tendencies in three separate factor analysis trials.
It was Tupes and Christal (1961) who repeatedly found five recurrent factors
when rating personality. Their study consisted of eight separate sample ratings on 35
personality traits first introduced by Cattell (1943). Participants in each sample varied in
education, length of acquaintanceship (3 days to over 1 year), and experience in
personality rating (novice to years of experience). Other variables included situational
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factors of fraternity, dormitory, or military training environments. Sample groups were
gender homogeneous with seven out of the eight samples exclusively male. Tupes and
Christal labeled five recurrent personality traits emerging from this study as (a) surgency,
(b) agreeableness, (c) reliability, (d) emotional steadiness, and (e) culture. Surgency, a
synonym to extraversion, was described as talkativeness, assertiveness, sociability,
cheerfulness, and adventurousness.
The development of the Big Five theory emerged almost simultaneously by
several researchers, with McCrae and Costa (1985) and Goldberg (1990) among the most
prominent. Those researchers approached personality through different methods, but all
arrived at the same conclusion that regardless of culture or language, there were five
personality traits common to all humans. Those five dimensions were a result of
analyzing thousands of questionnaires through factor analysis. It is important to
acknowledge that examiners of those five personality traits did not presume which traits
would emerge, however repeated findings dictated the consensus (Digman, 1990).
Today, the Big Five-personality theory is widely accepted by most researchers of
personality. These five basic dimensions of personality—neuroticism, openness,
agreeableness, conscientiousness, and extraversion—have been examined, verified, and
dissected by numerous researchers for their validity and reliability and have fared very
well. The five personality traits have been scrutinized by various instruments across
cultural, ethnic, and racial lines. Although there is considerable debate on the adjectives
and components that define these traits, most five-factor theorists agree that some
description of these five traits is a necessity when describing personality.
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Eysenck Personality Inventory/Questionnaire
Developed by Eysenck and Eysenck (1964), the Eysenck Personality Inventory’s
(EPI) focus is on two components of personality: extraversion/introversion and
neuroticism/stability. It comprised 57 yes–no items without replication of test questions.
The two dimensions of extraversion and stability are divided into four subsets: (a) stable
extraverts are those who are talkative, responsive, and carefree; (b) unstable extraverts
describe individuals who are high-strung, impulsive, and impatient; (c) stable introverts
display passive, even-tempered, and dependable; and (d) unstable introverts can be
moody, anxious, and inflexible individuals (Eysenck, 1968). Like the EPI, the Eysenck
Personality Questionnaire (EPQ; Eysenck, 1975) was generated as a counterpart to
Eysenck’s personality theory (Eysenck, 1964). It has been used extensively in
personality, social, and cognitive assessments and has plainly established usefulness in
the area of personality assessments. Adding a third personality dimension to the EPI, the
EPQ examined psychoticism, along with degree of extraversion and neuroticism,
presenting 100 items in a self-report questionnaire. Rocklin and Revelle (1981) asserted
the two assessments (EPI, EPQ) are correlated through the sociability factor rather than
the component of impulsivity. In an effort to refine the extraversion scale impulsivity
questions were removed from the EPI in lieu of sociability queries that determined degree
of empathy and hostility. However, critics have demonstrated a lower consistency in the
psychoticism scale than in the extraversion/introversion and neuroticism/stability scales
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(Rocklin & Revelle, 1981), implying the validity and reliability of this subset may be in
question.
Research on Personality and Learning
Kneipp, Kelly, Biscoe, and Richard (2010) studied student perception of quality
of instruction and the Big Five personality types in instructors. Their findings suggested a
significant correlation between the characteristic of agreeableness and student perceived
instructional quality, and while it was predicted that the trait of extraversion would result
in high teacher evaluations, that was not the case. Pishghadam and Sahebjam (2012)
examined the relationship between the Big Five and teacher burnout. Results suggested
that emotional exhaustion were consistent with the trait of extraversion and neuroticism.
The personal qualities of any instructor would manifest themselves through teaching
practices, regardless of common materials and syllabi (Carr, 2007). Blank (1970)
performed a study determining a positive correlation between instructor involvement and
student satisfaction. Therefore, the suggestion that instructor presentation was dependent
on personality was apparent; the precise connection has yet to be realized.
Patrick (2011) proposed an association between the Big Five personality traits,
student grades, course assessment, and student evaluations of teachers at the university
level. Findings supported the personality traits of extraversion, openness, agreeableness,
and conscientiousness as positive factors, determining a favorable evaluation, while
neuroticism did not. A relationship between students’ expected grades and course
satisfaction was described by Patrick, but no significant relationship to satisfaction with
42
the instructor was noted. Discrepancies between course and teacher evaluations were
attributed to instructor personality more so than grades or perceived learning, which
indicated that a student might have liked the course, but not the instructor.
In adding to the literature of personality traits, learning styles, and academic
achievement, Komarraju, Karau, Schmeck, and Avdic (2011) enlisted 308 college
students to complete the Inventory of Learning Processes and the five-factor inventory
model. Also collected were demographic information and GPA. Participants represented
all undergraduate classes enrolled in a variety of subject areas. Correlation and regression
analysis indicated various relationships. One relationship significant to this literature
review is that the trait of extraversion, along with openness, related positively to
elaborative processing, which consisted of connecting and applying new ideas to present
knowledge and personal experiences. Understanding the social aspirations of extraverts
might suggest that instructors with a greater extraversion dimension had the ability to
convey real-life scenarios and practical applications to their students. The aforementioned
study reiterated the contention that both learning style and personality traits influenced
academic achievements (Komarraju et al., 2011).
This study’s examination of instructor degree of extraversion and student learning
style attempts to rationalize a diligence toward grouping students according to learning
style by identifying levels of instructor extraversion that are advantageous for specific
learners. When the instructor's teaching style and personality match the student's learning
style, the chance for the student to learn more quickly and easily can lead to an increased
rate of degree completion.
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Extraversion: A Closer Look
According to McMillan, Groth, Lane-Getaz, Dittmann, and Bailey-Seiler (2012),
extraverts responded readily to positive stimuli. They announced findings on a study
conducted with 212 undergraduates (69 men and 143 women) with a mean age of 19.52
years. Participants were asked to complete the NEO-PI-R (Costa & McCrae, 1992), then
choose among various hypothetical scenarios of positive, negative, and neutral
circumstances; self-reporting data on personal characteristics; word preferences
describing the intensity or extremity of a word (stone verses pebble, for example); and
positive, neutral, or negative photographs. Results indicated that extraversion was
robustly significant to positive stimuli, while the components of warmth and positive
emotions also had a high correlation. Those results implied that instructors’ positive
responses to a class could be affected by the perception of a class being collectively
positive and pleasing to the instructor. The argument was then made that a class was
pleasing when attentive and engaged by learning in the style that was most comfortable.
Likewise, extraversion related positively to neutral stimuli, although not as much as
positive stimuli, and because there was no correlation between extraversion and negative
stimuli, the study did not confirm a relationship between extraversion and responding to
intense negative stimuli. However, Friedman, Förster, and Denzler (2007) suggested that
although positive affective states led to freedom and creativity, people with negative
affective states might perform better on a task considered important or serious. That
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implied that instructors who were serious in their teaching endeavors had introverted
personality types.
Extraverts have a positive well-being and satisfaction with life. The research
indicates a substantial correlation between extraversion and happiness (Wilt & Revelle,
2008). Falkenstern and Kwon (2012) examined that assertion, claiming the quality of
resilience was a significant variable mediating the outcome of happiness. Ninety-seven
participants were administered the extraversion subset scale of the Big Five, an egoresiliency scale, and a satisfaction with life scale. The participants were 76% female and
81% Caucasian. Findings, at a significant level, indicated that degree of extraversion
forecast the amount of resiliency and resiliency predicted satisfaction with life.
Ripski, LoCasale-Crouch, and Decker (2011) examined trait stability in
preservice teachers and found a significant reduction in the trait of extraversion during
training. Explanations for that result might be found in the increased confidence students
experienced as training continued, maturation developed, and the need for social
interaction declined as more responsibilities were acquired. Although the implications
that seasoned teachers experienced a reduction in extraversion was plausible, the stability
of the Big Five personality constructs had proven to be consistent in individuals over time
(McCrae & John, 1992).
Research on Teacher Personality and Student Outcomes
Patterson and Purkey (1993) defined good teaching as not a matter of teaching
method, but rather the personality of the teacher. They posited that teachers must be
genuine, open, and honest, and that such behavior—even when teachers become
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impatient, angry, or irritated—actually reduced educational difficulties. When teachers
were genuine, students knew who the teachers were and where they stood in areas that
affected them academically. Neff, Wang, Abbott, and Walker (2005) investigated the
influence that gestures and language variation had on students’ perception of instructor
extraversion, determining if a system of preplanned facial expressions, gestures, tone, and
mood of voice could predict the perception of the trait of extraversion. Findings agree
with the prediction of a statistically significant link between those paradigms of
extraversion, gestures, and language.
Simpson, Gangestad, and Biek (1993) investigated the relationship between
personality and nonverbal behavior. They videotaped 109 female and 101 male
undergraduates answering questions by an interviewer of the opposite sex. Considered
attractive by societal norms, those interviewers recorded each participant’s nonverbal
behavior on 11 behavioral actions and 34 global attributes. Students considered to be
extraverts laughed, smiled, and looked downward less often than those considered
nonextraverts; extraverts exhibited more flirtatious glances than those deemed as
introverted. In addition, extraverts rated high in self- monitoring, pretentious, socially
engaging, and dominating behavior than their less extraverted counterparts.
Students and instructors in yet another study were asked to rate the qualities of an
innovative teacher (Jaskyte et al., 2009). Fifty-two students along with 48 instructors
participated from 20 different academic departments. Students rated flexibility, attending
to different learning styles, humor, enthusiasm, and providing a relaxed atmosphere as
preferable qualities in an instructor. Students and instructors had similar results in the
46
areas of open-mindedness, contemporary examples, local and global events, differential
testing, and novelty presentation methods. Where those two groups differed was in
teaching methods and materials used. Student ratings were much lower than instructor
ratings in those areas, indicating that other factors such as teacher personality, classroom
culture, and student/instructor communication were valued in the learning environment.
Jaskyte, Taylor, and Smariga (2009) proposed that teacher personality played an integral
part in student ratings of innovational techniques. Regardless of materials used or
presentation methods, students yearned for an instructor who would entertain their
questions, address their concerns, and challenge their intellect. Technology ranked low in
both groups, implying a personal interaction was desired and the way in which material
was presented was more important to the student than the material itself.
Some students prefer strict teachers, while others like teachers who are flexible,
socially inclined to communicate, and humorous. Characteristics like respect, honesty,
sincerity, kindness, and confidence are also valued. Akbar (2009) conducted a survey
asking 346 students to describe the characteristics of an effective teacher. The aim was to
determine if students’ selection of a good teacher was dependent upon their own
personality trait of extraversion. Differences among introverts and extraverts were noted
by the following: Extraverted students preferred teachers of witty nature to other
teachers, while introverted students preferred teachers who accepted the ideas of students
and of other teachers. Moreover, students who were introverted preferred strict teachers
over other teachers. Ironically, introverted students preferred teachers who had flexible
behaviors over other teachers (Akbar).
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Maximizing an instructor’s ability to convey information is essential. A factor in
this maximization is the students’ desire for honesty and genuineness (Jaskyte et al.,
2009). In addition, students’ preferences for instructors varied from humor and affability
to acceptance and tolerance of others (Akbar, 2009). Determining if student preferences
are encouraged by linking learning modalities to instructor level of extraversion is one
consideration of this dissertation. Other considerations for future research entail the
investigation of learning modality groups in contrast to controlled groups; an examination
of the other Big Five personality characteristics of openness, conscientiousness,
neuroticism, and agreeableness in regard to learning style modalities; and the exploration
of learning style modalities in connection with the degree of self-extraversion. It should
be the practice of every learning institution to place students in the best possible
environment, with the most favorable instructor, and the appropriate
materials/instruments for their style of learning.
Gardner’s Theory of Multiple Intelligences
Gardner’s theory of multiple intelligences (TMI) (Gardner, 1985) is intriguing,
and yet, many have criticized his findings. Gardner presented elements of intelligence as
linguistic, logical/mathematical, spatial, musical, body kinesthetic, interpersonal,
intrapersonal, and naturalistic skills, and admitted that TMI might have to be expanded to
incorporate new intelligences. Many scholars had separated intelligence into different
categories, contending that an individual might be competent in one area, but not in
others. Moreover, society demonstrated that people who were considered very intelligent
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in one area were inept in another. That notion could be recognized in individuals with
specific talents, from analytical thinking to the mastery of social interactions. Still, others
were exceptional in creative endeavors or observational skills (Sattler, 2008).
According to Gardner (1985), an individual with pronounced interpersonal
intelligence understood the objectives, needs, desires, and motivations of others. They
had the ability to connect with others by recognizing the similarities and differences
among people. “Interpersonal individuals are usually extraverts” (Furnham & Mansi,
2011, p. 3). Extraverts were empathizers, which promoted caring and supportive
interaction. They were also sensitive to facial expressions, voice intonations, and physical
gestures, maintaining close relationships with friends and family members. On the other
hand, intrapersonal people were primarily introverts ((Furnham & Mansi, 2011).
Gardner (2000) described intrapersonal intelligence as understanding one’s own
beliefs, attitudes, moods, and ideas. Those individuals had a real understanding of their
own strengths and weaknesses. Unlike the extraverts who had a sense of other’s emotions
and motivations, the introverts had a sense of themselves; their likes, dislikes, thoughts,
feelings, and goals were all at the forefront of their being. They were self-motivated and
could often concentrate on a concept, subject, or topic by themselves. Introverts shied
away from groups and learned best through observing and listening.
One criticism of Gardner’s TMI was the inability to test some intelligence in the
same way as others (Gardner & Moran, 2006). Sensory-perceptual aptitudes, such as
verbal, number, word articulacy, perceptual promptness, space/visualization, and
mechanical intelligence could be influenced by standard cognitive psychological and
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social psychological research mediation prototypes. They could be easily observed
experimentally. Contrastingly, the testing for other non-concrete categories like
interpersonal and intrapersonal abilities were viewed as sketchy at best (Hunt, 2001).
Although Gardner had never prescribed an exact educational formula derived from
TMI, his suggestion that individualized instruction and approaches to topics from
different perspectives had generated the interest of many in how individuals learn and
what makes us intelligent. His theory was useful to broad and applied audiences, and it
was positively welcomed in school settings, where an abundance of kids already fail.
Critics argued that Gardner’s contentions were too broad. Gardner countered back,
stating that behaviors studied were simply too narrowly defined to qualify as human
intelligence (Gardner, 1985). Barrouillet, Bernardin, Portrat, Vergauwe, and Camos’s
(2007) speculation of numerous possible cognitive processes lent itself to the validity that
human beings were indeed complex and unique. Instruction should be individualized
whenever possible, however the feasibility of individual instruction was improbable.
Gardner’s (2000) theory was vital in promoting a continuous search for various
intelligences in all animal species. Modern psychological assessment of learning had
embraced science with flexibility and acceptance, knowing that intelligence could not be
fully or even meaningfully understood outside its cultural setting. Research on
intelligence within a distinct culture might be unsuccessful at its attempt justify the array
of awareness and skills that might constitute intelligence for that particular culture.
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Learning Styles
When examiners first investigated with learning-style prescriptions for teaching
college students, significantly greater attainment resulted (Hein & Budny, 1999;
Kamuche, 2005). Those improvements were evidenced in several subjects—marketing,
mathematics, anatomy, physiology—and across subjects (Taylor & Elias, 2012).
According to Dunn (1990), there were dominant preferred learning models in every
individual. Those learning models were on a bi-polar continuum, where each modality
(auditory, visual, and kinesthetic) was evident to some degree and would mesh with the
other models in producing a learning style that was unique to the individual. Brooks and
Khandker (2012) reiterated that assertion by pointing out that everyone had a dominant
learning strength. Although other modes of learning were evident, research confirmed
that accommodating that strength produced a student who could grasp information
quicker, retain it longer, and apply it more effectively than learning styles less dominant
when placed in an instructional environment conducive to his/her learning style.
Honigsfeld and Dunn (2006) put several justifications forth in identifying learning
style among groups. Those were as follows: (a) Adult males and females differed
significantly in learning style paradigms. On a global scale, females were found to be
more auditory, persistent, driven, and accountable than their male counterparts. Women
also required more diverseness in instruction. (b) Students with higher grade-point
averages had considerably dissimilar styles from those with grade-point averages below
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normal. While high achievers were described as gravitating toward a traditional
classroom environment—a quiet place, bright lights, minimum distractions, studying in
solitude, or with a facilitator present—low achievers favored learning environments with
conversation in the background or music softly playing. Their preference for studying
also included a couch, easy chair, frequent breaks, and the presence of food or drinks. (c)
Learning styles also varied by age, with older adults who returned to school after having
life experiences demonstrating a significant learning style preference from younger
adults. (d) No two adult students would approach the same task with identical strategies.
Some might read and highlight everything considered important, while others spent their
time searching the Internet, and still others would listen to taped lectures while
performing other tasks.
Combinations of learning processes might be intermittently interwoven in a
student’s repertoire of appealing ways to learn. People consistently utilized the strategies
that worked best for them. When various methods were not provided, many students
became overwhelmed, discouraged, disheartened, and unable to cope with higher
education challenges. They settled for less than their capabilities dictated, becoming less
confident, less motivated, and more compliant with the status quo (Honigsfeld and Dunn,
2006)
VAK model.
Dunn, Dunn, and Price (1985) described learning style in the way a person was
able to digest new and difficult knowledge. The VAK model originated from 30 years of
work, involving almost a century of research on how people learn differently, by
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professors Rita and Kenneth Dunn in the 1970s. The controlling premise was that there
were distinct differences among learners with implications that academic achievement
was attained through relatively fixed categories and that certain factors added to or
detracted from learning successes. Those categories were as follows:
1. Environmental—sound verses quiet, temperature of the classroom setting, and
formal verses informal seating arrangements.
2. Emotional—being motivationally consistent verses inconsistency, and
conformity verses nonconformity.
3. Sociologically—in cooperative pair or group activities, as compared to set
routines.
4. Physiologically—the student connected by auditory, visual, or by kinesthetic
means. There was a time of the day when a student would display low or high energy
levels, or could sit for long periods of time verses the need to move and be active.
According to the VAK theory, one or two of our sensory receivers were
prevailing, suggesting that learners had a natural partiality for the way they learn. As
such, there should be a compulsion for matching teaching styles with learning styles to
enhance the learning progression, enabling teachers to address the requirements of
learners in a more efficient manner. Yet, one style of learning might not always be the
same for some tasks. Moreover, as the concept evolved, research came to support the
application of an assortment of modalities in the course of instruction, instead of a single
learning style. A learner might prefer one style of learning for one task, and a mixture of
styles for a different task.
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The core value of the VAK learning theory was to enable people to think in terms
of various representational arrangements. By combining different instruction techniques
and rationalizing about the diverse ways in which we process material, instructors could
start to develop a multisensory learning environment. Rather than adapting instructional
techniques to each individual, a combination of coinciding stimuli would enable a
learning group to improve their storage, retrieval, and clarification of information.
Centered on three main sensory receivers (audio, visual, and kinesthetic), that model was
considered imperative in determining an individual’s learning style.
Visual. The visual learner preferred to observe, rather than talk. Naturally quiet
by nature, reading might be appealing to them. They memorized by transforming mental
images into visual ones. Charts, graphs, films, and demonstrations were all conducive to
that type of learner. Consequently they could easily lose focus by visual distractions.
They noticed detail, enjoyed the use of color, might have good handwriting skills, and
likewise, draw or doodle. They remembered first impressions and faces, and might
sometimes stray away from verbal conversations.
Auditory. The auditory learner had an outgoing personality. They loved
conversing and social situations. They might even talk aloud to themselves in clarifying
events or circumstances. They were easily distracted by noise. They might like to be read
to and might pay particular attention to an individual’s choice of words in conversation.
Their memory usually followed sequential steps and might find singing or humming
appealing while completing tasks. Written instructions could be problematic.
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Rather than faces, the auditory learner was more prone to remembering names and could
many times recognize people by voice. Being aware of rhythm, they enjoyed music and
the sounds of others’ voices and could oftentimes mimic another. The auditory learner
might absorb more upon verbal repetition of an explanation than the visual or kinesthetic
learner.
Kinesthetic. Kinesthetic learners could be fidgety and liked to be in motion most
of the time. They might tap a pencil or their foot when contemplating an idea. They were
naturally outgoing and expressed themselves in physical ways. Reading was not a
favorite past time, and therefore, they might find spelling difficult. They thrived in
remembering what they had done, rather than what they had seen, heard, or said. The
kinesthetic learner solved problems by working them through physically, if possible.
They learned and memorized by doing, having good reflexes and timing. They enjoyed
activities and the physical handling of objects. The kinesthetic learner liked to touch and
use gestures while talking and was usually open for new ideas.
VARK Model.
The VARK (visual, auditory, reading/writing, and kinesthetic) model was similar
to the VAK model, but included the learning modality of reading and writing (Fleming &
Baume, 2006). The development of that model rested on the premise that some learners
had a preference for writing material, while others preferred symbolic representations of
material such as maps, graphs, and charts. Online questionnaires of 13 proposed
questions were administered to over 180,000 people during a 6-month period in 2006.
Participants were encouraged to reflect on their VARK results with their own
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perceptions of how they learn. Outcomes reflected a 33% match to student perception of
their learning modalities. Although that percentage was not high, positive feedback was
substantial. One criticism of the VARK model was that it was hard to statistically
validate, which meant it could be problematic in research. Rather, its value lay in helping
individuals to think about personal degrees of learning modalities and give options for
learning not previously considered. Fleming and Baume conceded to that discrepancy,
but pointed out there were currently no instruments that gave reliable readings because
the constructs of learning styles were numerous and complex.
Genetic Component of Learning Styles
Binoy (2012) conducted a study involving monozygotic twins using the VARK
model. Usual factors that determine learning preferences—heredity, gender, heredity,
age, and culture—were constant because of the nature of the study, however a significant
difference of learning styles was found to hold true regardless of genetic sameness.
Although many more studies of this kind are called for, it seems that environment
overrides genetics in learner preference.
Dunn, Beaudry, and Klavas (1989) emphasized a biological component in
connection with learning styles and contended those who ignored that presupposition
were naïve. Offered was the suggestion that left brain individuals (those who were
analytical and used deductive reasoning) learned in small steps, and that right brain
individuals (those who perceived concepts on a global scale and used inductive
reasoning) learned in broader phases before considering details. After an examination of
studies, they concluded that right brainers in grades five through twelve preferred
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working with music, in groups, informal seating arrangements, and with kinesthetic
rather than auditory or visual resources. Left brainers preferred a formal, structured,
classroom, and visual, rather than kinesthetic, methods of instruction. In considering
adult community college students, those with more right hemisphere brain activities
preferred sound, intake, mobility, and kinesthetic procedures more often than their left
brain counterparts, who gravitated toward formality and bright lights. Consequently,
differences of learning style preferences were identified between age groups and those
with similar interests and talents. Interestingly, when inquiring into culturally diverse
groups and family dynamics, researchers found more variances and dissimilarities than
resemblances.
Learning Style Preferences
Kazu (2009) wanted to determine the effect of learning styles on education and
the process of teaching. He examined various learning styles and their merit in the
educational system. The consensus was that learning styles were a particular way in
which an individual acquired, processed, and maintained data, mostly stable and
unchangeable but could be developed by experiences over time. Kazu reiterated the
importance of learning styles by proclaiming its positive effect on the learner: instilling
confidence and promoting autonomous learning throughout the educational environment.
Conclusions to that study revealed that individuals learned differently, and those
differences should be followed in the teaching environment.
Eysenck (1998) reviewed literature suggesting that children with a large dose of
the trait of extraversion would benefit from discovery learning, where the learning
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environment was flexible and uninhibited. Those who were more introverted would
benefit from reception learning, where the learning environment was controlled and free
from distractions.
According to a study by Fang (2012), the mismatch between teaching styles and
learning styles was evident and therefore deserved attention. The problem arose when
that mismatch created an obstruction to learning. The aim was to reduce possible
incompatibilities between teacher and student by making the teacher cognizant in
designing various teaching strategies to accommodate all learners. Participants included
157 second-year college students in the humanities and science fields, with a mean age of
19.5 years (81 females and 76 males), and four English professors ranging in age from 26
to 42 years old. The survey consisted of 65 statements, measured on a Likert scale (1 =
almost never, 2 = rarely, 3 = sometimes, 4 = often, 5 = almost always). Thirteen
dimensions of learning styles were measured. A survey was also administered to evaluate
the instructor’s teaching style preferences. Results indicated the common learning style
preferences among students were visual, independent, global, random, and reflective, in
order of highest percentages, while English instructors were prone to the visual,
independent, group-oriented, sequential, and reflective styles of teaching.
An evaluation of 36 studies between 1980 and 1990 conducted on the Dunn and
Dunn model by Dunn, Griggs, Olson, Beasley and Gorman (1995) evaluated learning
styles preferences of 3,181 participants. Results indicated that accommodating students’
learning style would yield a 75% increase in the standard deviation from those who had
not been provided with a learning style accommodation. Implications of that meta-
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analysis divulged that when students’ learning style was considered and matched with
educational interventions equipped to satisfy those learning styles, academic achievement
was bolstered.
In a study conducted by Terregrossa et al. (2012), an examination of the influence
of learning styles on introductory accounting and economics courses was conducted
using the Building Excellence (BE) learning survey. That survey, similar to the Dunn and
Dunn model (Dunn et al., 1990), was comprised of 6 categories and 26 learning style
elements. Results proposed evidence that college students’ academic achievement was
significantly correlated to their dominant learning style. Furthermore, that study
substantiated the notion that learning styles appropriate for a particular discipline
(accounting students) might not satisfy the majority of another discipline (economic
students). In other words, the type of subject taught might influence the type of leaners
taking the course, and inevitably, the way in which the course should be taught.
Regardless, it was obvious that a unilateral approach to teaching was inefficient and
insufficient; therefore various pedagogical techniques were crucial in reaching all
students. The suggestion of corresponding student learning style to instructor teaching
style was prevalent in that study’s findings throughout the academic community for any
academic discipline.
Kamuche (2005) investigated the link between learning styles in statistics students
and the teaching style of instructors, developing a hypothesis that students whose
learning style was similar to an instructor’s teaching style would perform better on
assessments than those who were dissimilar. They would earn higher grades and would
59
have a better understanding of the subject matter, and test performance would correlate
with the grade earned. The study lasted for 3 years, from 2002 to 2005, and involved a
range total from 105 students the first year to 1,265 in the third year. Results
demonstrated a high correlation between student learning styles and instructor teaching
styles, along with grade correlation. Simply put, the evidence clearly showed that
students performed better when their learning style was paired with a teacher of similar
teaching style. Conducting this research on instructor degree of extraversion and student
learning style may imply that an instructor’s level of extraversion produces a particular
teaching style, resulting in the suggestion that grouping students according to learning
style improves academic achievement.
Learning Styles Assessments
The Kolb Learning Style Inventory (Kolb, 2005) was based on the experiential
learning theory. Its premise relied on learning as a process of thinking, feeling, behaving,
and perceiving in relation to everyday experiences. It was a holistic process that involved
creating knowledge through the assimilation of new experiences with prior ones. It
integrated concrete practices with abstract conceptualizations and reflective thought with
active experimentation in producing a fully engaged learner. Individuals might gravitate
toward one component of experiential learning, as opposed to another, or might use all
four components in different orders. An example would be learning how to ride a bike.
Some might want to read about how bike riding was performed, the placement of the
hands, and the speed at which one should go, and the tilt of the handlebars, while others
might want to watch a demonstration of someone riding a bike. While still others might
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just want to get on and go, knowing that every fall or mishap would teach them what to
do or not to do. The experiential learning theory took into consideration the VAK and
VARK models, but went further in suggesting that the capabilities of a learner in the
auditory, visual, and kinesthetic fields were promoted and influenced by direct personal
experience with the task at hand.
Kolb identified four types of learners within that realm of experiential theory:
assimilators (who adhered to logical principles), convergers (who thrived on practical
applications and concepts), accommodators (who gravitated toward hands-on
experiences), and divergers (who liked to absorb a wide range of information).
Experience had always been a practical and efficient way of learning. Internships,
apprenticeships, and residencies all pointed to the concept of replicating best practices.
Kolb (2005) contended the usefulness of experience in the reinforcement of ideas was
better served in a curriculum than creating novel ones. The complex notion of Kolb’s
learning theory is far beyond the scope of this dissertation. However, its connection to the
rudimentary learning components of visual, auditory, and kinesthetic learning styles
should not be ignored.
Limitations
Brooks and Khandker (2012) asserted that a comprehensive approach to
pedagogical processes was merited due to the complex structure of learners and the
overabundance of teaching models. Their research involved matching the right and the
left brain hemisphere thinking preferences of the student to the right and the left brain
hemisphere thinking preferences of the instructor. Results indicated no significant
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preference according to final grades received. “…[T]he case for matching students to
instructors in order to improve student learning is tentative at best, and at worst it is a
large drain on resources” (p. 14).
The debate about the existence of learning styles, what types, and how many
continues forward. I propose that the auditory, kinesthetic, and visual styles of learning
are a given, and that these styles of learning can be enhanced through the right instructor
on an extraversion continuum. The variables in testing the hypothesis of instructor
extraversion and student learning styles are countless. Some teaching methods may be
better in some subject areas than in others. A student’s unique mixture of learning style
combinations varies widely. Professors, regardless of personality, can be more skilled in
pedagogical methods than other instructors. Student interests must also be taken into
account. In this literature review, I do not attempt to dispute or concur with past and
present literature on teacher personality and student learning styles, but my intention is to
increase and supplement prevailing opinions and assumptions.
Implications of Past Research on Present Research
Past research entailed primary personality characteristics that all individuals
possess to one degree. Jung’s (1959) work with archetypes and Eysenck’s (1975) insight
into the trait of extraversion grounded other studies in personality. The question of
ingratiating character into the academic realm was a complicated task. Future research
should focus on understanding teacher characteristics and what their relationship is to
academic success in the learning environment. Eysenck (1998) proposed an examination
of student personality and its role in the teacher/learner process. Polk (2006) contended
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investigating into various teachers’ personality traits might provide insight into the
ultimate possibilities of achievements for learners. Sun (2012) described a mismatch of
student learning style and teaching presentation as contributing to problematic conditions
of anxiety and negative attitudes among students and instructors alike. Wilt and Revelle
(2008) suggested one objective should be an examination into extraversion and student
academic functioning.
Summary
The connection between instructor extraversion and learning styles can be
envisioned by various means. Some conjectures are that extraverted teachers are prone to
verbal communication, and therefore, are better for auditory learners; introverted
instructors connect with visual learners because they encourage them to do cooperative
learning, leaving the instructors as observers more than participators, or that introverted
teachers are better with kinesthetic and visual learners because of the lack of social
communication desired.
Jung (1959) developed the notion of the self and its entities, while Eysenck (1975)
fine-tuned Jung’s work into a more concrete definition. Biological factors concerning the
trait of extraversion were corroborated (DeYoung et al., 2010; Luo et al., 2007; Omura et
al., 2005), implying the trait was inherent, an integral part of personality and usually
established and ingrained in a persona from birth. Garner’s theory of multiple
intelligences (Gardner & Moran, 2006) dictated consideration of similar established
human traits, where skill and proficiency were a mixture of specific intelligences, a
combination of innate and learned factors producing a distinctive individual. The
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matchup of those traits during the teaching and learning process was a feasible solution
to increased productivity and less confusion. The VAK (Dunn et al., 1985) and the
VARK (Fleming & Baume, 2006) learning style models simplified and categorized
learning methodologies into practical and all-inclusive dimensions of cognitive
absorptions. Although everyone had degrees of each learning style, a dominant
preference should appear in most. This particular study contributes to the literature by
conceptualizing alternatives to teacher/student dynamics.
In Chapter 3, the research methodology is presented in its entirety. The purpose
of this study is considered, instruments are examined for validity and reliability,
participants are described and procedures are reviewed. Data analysis techniques are
presented and ethical considerations are discussed.
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Chapter 3: Methodology
Introduction
Chapter 3 is an overview of the practices and procedures utilized to conduct this
research. The design, as well as a justification, for choosing this particular type of
strategy, are detailed throughout this section. Participants’ demographics and certain
characteristics are discussed, along with setting and context of the research environment.
A detailed description of the administration process are covered, as well as the ethical
and moral considerations given to this project. The procedures and instruments used in
measuring the results are examined, accompanied by a rationale for the chosen statistical
method. Validity and reliability of these instruments are inspected in an attempt to
substantiate findings.
Purpose of the Study
The examination of teacher instructional methods and student learning has been
approached from unlimited perspectives. Investigations by researchers involved the skill
and training of instructors, in addition to the constructs of personality, setting,
demographics, age, culture, and race of both instructor and student. The purpose of this
study was to observe correlations between the instructor’s degree of extraversion and
student learning style. The purpose of this study is to contribute to pedagogical practices
by presenting an approach to embracing innate traits that produce a particular type of
teaching strategy geared toward a certain type of learner. Zhang (2006) proposed the
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appropriate match between teacher and student could yield tremendous results for both
parties, and although this suggestion has provided a variety of literature for many years,
unchartered territory abounds.
Research Design and Approach
This research study may indicate a relationship between degree of instructor
extraversion and the dominant learning styles of visual, auditory, or kinesthetic learners.
A cross-sectional correlation design was implemented to determine the strength of that
relationship. A cause and effect relationship is not assumed, but results of data may imply
an association between instructor extraversion and student learning style.
The population in question in this research was community college instructors and
students. My intention was to examine associations between instructors’ degree of
extraversion and student learning styles with the aim of generalizing to the larger
population. By using a cross-sectional approach, I attempted to reflect a true
representation of community college students and instructors in the learning and teaching
environment. Findings may be applicable to other community college environments.
Although a qualitative analysis could result in detailed information on particular cases, it
would be subjective in nature and not generalizable to the community college population,
and therefore, qualitative analysis was not appropriate for this study. Empirical data are
necessary in order to show significance, validity, and reliability.
Data gathered during the school term on demographics, learning style preferences,
observer-rated instructor extraversion, and instructor preference were analyzed. These
multiple factors were examined for any significant correlations.
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Setting and Sample
Participants
Students volunteering for this study were recruited from a community college
district in a southwestern region of the United States. This community college district has
an enrollment of approximately 10,000 students seeking associate degrees and certificates
in various areas of the Arts and Sciences. Permission was sought from the chair of the
Psychology Department at a community college and the dean of Arts and Sciences at yet
another community college. Both colleges are affiliated with the community college
district in a southwest region of the United States. The students participating in this study
were enrolled in one of these two colleges as part- or full-time students. Participants were
selected on the following criteria: (a) availability, (b) proximity, (c) willingness to
participate, (d) 18 years or older, (e) part- or full-time student, and (f) ability to read and
comprehend the English language. The community college district designated for this
study comprises 61.3% Hispanic, 28.9% Caucasian, 6.4% African American, and 3.4%
other. Specifically, the two community colleges utilized in this study have similar
racial/ethnic demographics, with mean percentages of 54.5% Hispanic, 31% Caucasian,
9.7% African American, and 4.9% other (Texas Higher Education Coordinating Board,
2012). A sample size of approximately 300 students was taken from this population.
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In order to examine these hypotheses, I distributed observer extraversion
inventories, Barsch Learning Style Inventories (Barsch, 1996), and a demographic
questionnaire to community college participants in the southwestern United States.
I presented the project in the dialogue that follows:
I am conducting a study in pursuit of completing my Ph.D. in educational
psychology. Your help would be greatly appreciated by completing a short
(approximately 15 minutes in length) inventory. My aim is to examine
relationships between a student’s learning style of auditory, visual, or kinesthetic
modalities and the level of instructor personality. The question is whether an
instructor’s level of extraversion is conducive to or detracts from a student’s
natural inclination of acquiring information. In other words, is it possible that the
instructor from whom you learned best presented material in an instinctive way
that naturally fit with the way you learn? Could this presentation style be
influenced by the instructor’s personality?
I would like to enlist the help of all students 18 years of age (or older) by
completing 3 surveys. One survey asks for demographic information, another asks
for information about a past teacher and the third survey asks about your learning
styles. This could be an instructor who you like, but not necessarily. Rather, think
of an instructor who you consider a good teacher, someone you thought explained
well or made you think.
Next, there is a learning inventory determining your dominant learning
style. In an attempt to find the answer to this question, I am asking that you
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complete the questionnaire in its entirety so as to eliminate “missing data” barriers
and to obtain valid and reliable data. Please DO NOT put your name on the packet
I will be handing out. All individual information is anonymous and only group
results will be published. However, if you would like to know your individual
score, you may do so by contacting me at my e-mail address (keeping in mind that
your e-mail address may reveal your identity).You must have your inventory
number (shown on the front of the packet) to request your score. Participation is
strictly voluntary, and there is no benefits or consequences attached to your
participation. Nevertheless, if you would take a few minutes at this time to
complete the inventory packet, I would be forever appreciative. Thank all of you
in advance for your contribution to what I hope will shed some insight into
student/instructor compatibility.
Administering Procedures
Permission was sought to distribute inventories at the beginning of a class
session. Given instructor approval, a brief introduction of the purpose and significance of
this research was addressed along with an open invitation for anyone over 18 to
participate. A packet containing informed consent (see Appendix A), the Barsch Learning
Style Inventory (Barsch, 1996), demographic information, and a short observer rating
scale of an instructor’s degree of extraversion was distributed. This instructor could have
been from the students’ past or present, but one who the students felt had taught
exceptionally well. An e-mail address was provided to answer any questions posed by
participants. With this approach, a sufficient amount of data collection was obtainable in
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a quick and efficient fashion. Those willing to partake did so strictly by choice. If an
individual chose to complete the survey, a stamped self-addressed envelope was provided
for mailing. Participants are identified by number and not by name on the inventories and
may be informed of the results on their learning style, if requested. The number notated
on the students’ inventory packet would have to be identified to the researcher before any
information could be released. Therefore the participants were asked to write down the
inventory number if they would like to know their learning style score at a later date.
Instrumentation
BFI
The Big Five Inventory (BFI) was introduced as an alternative to multi-item
personality instruments in the late 1980s (John, Donahue, & Kentle, 1991). Consisting of
44 items, the BFI measures personality traits of openness, extraversion, neuroticism,
agreeableness, and conscientiousness. Although these personality constructs are broad
measures of personality, they have proven to be universally consistent (Heine & Buchtel,
2009). For this study, only items defining the extraversion trait was employed, which are
eight adjectives or adjective phrases that can be answered on an observer rating scale (see
Appendix B). The domain scales of the BFI have demonstrated consistent reliability, high
convergence with other personality scales, and a high self-peer correlation (John,
Naumann, & Soto, 2008). According to Rammstedt and John (2007), the extraversion
trait is a Big Five trait that is effortlessly identifiable in others even when encounters are
brief. The BFI assessment has proven to be psychometrically sound by having internal
consistency, reliability, and validity (Young & Schinka, 2001). Rammstedt and John
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(2007) affirmed that the reliability and validity of the BFI-44, and the BFI-10 scales are
comparable to the NEO-PI-R, where convergent and discriminant validity correlations
were considerable.
Instructor level of extraversion was ascertained through students’ rating on the
BFI inventory, where students rated their chosen instructor. The BFI extraversion items
are 1, 6R, 11, 16, 21R, 26, 31R, and 36. Points were credited according to the scale of
strongly disagree—1 point, disagree—2 points, neither agree or disagree—3 points,
agree—4 points, and strongly agree—5 points. Items 6, 21, and 31 were negatively
scored items, and points were deducted from the number 6. An example would be if Item
21 were scored as strongly agree—5 points, then these 5 points would be deducted from
the number 6, resulting in a score of 1 for that particular item. Scores from the 8
questions on instructor extraversion, reported by the students, were entered into SPSS
with syntax instructions to obtain a total score for extraversion.
Permission was granted by the Berkeley Personality Lab to utilize its version of
the BFI in conducting this research. The Berkeley Personality Lab is an institution whose
purpose is to examine personality constructs, individual differences, and self-perception
as it relates to societal and environmental factors (John et al., 1991). The BFI is one
measurement among different scales that the Berkeley Personality Lab provides to
researchers free of charge and with minimum restrictions.
BLSI
The Barsch Learning Style Inventory (BLSI) has an item list of 24 questions
designed to identify visual, auditory, or tactile modalities in the secondary or college
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level learner (Barsch & Creson, 1980). The BLSI is an informal, self-report instrument
that detects relative strengths and weaknesses along different sensory channels (Appendix
C). Barsch and Creson credited the BFI with identifying learning modalities in specially
challenged students. A scale of often, sometimes, and seldom was presented as options to
the learner in avoiding either/or alternatives. The 24 items were scored according to the
type of item and the degree of response, and then computed to reveal a visual, auditory,
or tactile/kinesthetic strength. The BLSI is designed for ages 14 to adult and usually takes
between 5 to 10 minutes to complete. Based on the popularity of the BLSI, the research
contained in the Handbook of Mental Measures (Barsch & Creson, 1980), and the
recommendation of the International Personality Item Pool website (n.d.), the Barsch
Learning Style Inventory (Barsch, 1996) was chosen to assist in this research.
The BLSI identified pre-existing learning style variables of community college
student participants as auditory, visual, or kinesthetic/tactile. Scoring of the BLSI
consisted of attributing point values to the 24 questions pre-identified as having either
auditory, visual, or kinesthetic significance. Questions 2, 3, 7, 10, 14, 16, 20, and 22 were
scored as visual learning preferences; Questions 1, 5, 8, 11, 13, 18, 21, and 24 as auditory
learning preferences; and Questions 4, 6, 9, 12, 15, 17, 19, and 23 as kinesthetic learning
preferences. Points were credited according to participant answers of often—5 points,
sometimes—3 points, and seldom—1 point. Points were calculated under each learning
style category, with the higher score representing the dominant learning style.
Although a minimal amount of data on the reliability and validity of the BSLI is
available, it is extensively used by universities and colleges on a global scale
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(Heaton‐Shrestha, Gipps, Edirisingha, & Linsey, 2007; Sizemore & Schultz, 2005).
Kratzig and Arbuthnott (2006) reported ample reliability of the BSLI, with Cronbach’s
alpha 0.54 for visual and 0.56 for auditory.
Demographics
A demographic survey taken from the U. S. Census Bureau (2010) was
administered to students with 3 basic questions of age, race/ethnicity, and gender
(Appendix D). Five age categories were given values of 1 through 5 as follows: 18–20
group 1, 21–25 group 2, 26–35 group 3, 35–54 group 4, over 55 group 5. With the
exception of group 5, there is a 7-year span in each age category. Age groups were sparse
in numbers as age increased due to a relatively smaller number of older adults attending
community colleges than younger adults. According to the American Association of
Community Colleges (2013), the average age of a community college student is 29 and
approximately 82% of the faculty is over the age of 40. Terracciano, Costa, and McCrae
(2006), described personality traits as relatively stable at about age 30 and plateauing
around age 50. Instructors designated by students as skilled in their teaching abilities
should have relatively stable personality traits, as well as some student participants.
Race/ethnicity was divided into 5 categories of Caucasian, African American,
Hispanic/Latino, Asian, and Other.
The Research Hypotheses
Is there a relationship between instructor level of extraversion and a student’s
capacity to learn with a visual, auditory, or kinesthetic learning style? The hypothesis
asserted is that student preference for an instructor is influenced by the student’s learning
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style and the teacher’s level of extraversion, therefore the following hypotheses are
proposed:
1. H0: There is no relationship between teacher extraversion and student’s dominant
learning style.
H1: There is a relationship between teacher extraversion and student’s dominant
learning style.
2. H0: There is no relationship between teacher extraversion and visual learning style
scores.
H1: There is a relationship between teacher extraversion and visual learning style
scores.
3. H0: There is no relationship between teacher extraversion and auditory learning style
scores.
H1: There is a relationship between teacher extraversion and auditory learning style
scores.
4. H0: There is no relationship between teacher extraversion and kinesthetic learning
style scores.
H1: There is a relationship between teacher extraversion and kinesthetic learning style
scores.
Data Analysis
As stated in Chapter 1, the research hypotheses for this study are described in
detail to determine if there exists a correlation between the processes in which an
individual learns (auditory, visual, or kinesthetic) and the degree of extraversion in the
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instructor. A one-way ANOVA was performed on the extraversion scores and the scores
for visual, auditory, and kinesthetic learning styles. Mean values of teacher level of
extraversion were correlated to dominant learning styles. A Pearson correlation was
performed on each learning style category (auditory, visual, and kinesthetic) and
instructor extraversion scores to determine any significant relationships among those
variables. The mean and standard deviation of instructor extraversion and each of the
three learning styles (auditory, visual, and kinesthetic) were examined for any
significance. Data were keyed manually into the SPSS program under the variables of
gender (male = 1, female = 2), and race (Caucasian = 1, African-American = 2, Hispanic
= 3, Asian = 4, and other = 5).
Correlations were examined with regard to age, race/ethnicity, gender, and
learning styles. A sample size of 302 students was calculated using Cohen’s D, with
anywhere from 49 to 161 subjects in each learning style category, an alpha of .05, a
medium effect size of .30, and a power level of .80. Cohen (1988) described medium
effect size as one “large enough to be visible to the naked eye” (p. 26). In addition,
Chaun (2006) described an alpha =.05 as standard practice in academic research.
In considering external validity, it is recognized that the sample population was
recruited from the southwestern region of the United States and may not be an exact
representation of community college students in other regions of the country. Likewise,
this study attended to the dynamics of Western culture and may not be universally
applicable. In addition, internal validity threats may arise from participants’ inaccurate
responses due to poor recall of past instructors and their teaching methodologies.
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However, given the instruments chosen for this research, statistical validity was not
compromised.
Ethical Considerations
Consent was obtained from all subjects before administering inventories. Ethical
considerations were conveyed by the researcher and addressed in the consent form
(Appendix A). Participants were informed of the nature of this study prior to seeking
their consent. At no time did I attempt to conceal information or deceive participants.
Participation was strictly voluntary, and subjects’ consent was sought without
repercussions or incentives. Participants were also informed that they may discontinue
participation at any time without consequences. Paper copies of raw individual data will
be kept confidential and will be warehoused with and privy solely to me. Each survey
was assigned a number whereby the participant may refer to this number when inquiring
about results. Information will not be released to third parties without participant consent,
although group data results may be made public. Participants were 18 years or older.
Neither I nor this study are affiliated with the educational entity that participated in this
study. Subjects were not manipulated in any way or form, eliminating many ethical
concerns or interferences.
Summary
Chapter 3 outlined the process of examining the research question. Participants, variables,
instrumentation, recruitment process and data analysis were addressed in detail. A
correlational design approach was applied to the variables of extraversion, learning styles
and demographics. Data was collected and keyed into SPSS. Chapter 4 is comprised of
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the data collection process, statistics, and the findings of this research. Verification and
analysis of the data will be addressed and correlations identified as appropriate. Chapter 5
is a discussion of findings and conclusions with recommendations for further research.
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Chapter 4: Results
Introduction
This study’s objective was to examine correlational relationships between an
instructor’s level of extraversion and a student’s dominant style of learning. The
instructor, chosen by the student, is one considered to be effective in his or her teaching
techniques. Specifically, in this study I investigated whether or not an instructor’s
extraversion level is more advantageous in teaching an individual with a dominant
auditory, visual or kinesthetic learning modality. The purpose of this chapter is to present
the results of this study by discussing the data collection process, data organization and
results. Analyses consist of conducting descriptive statistics, Spearman correlations,
independent sample t tests, a one way ANOVA and Pearson correlations.
Data Collection
Data collection began upon receiving approval from the community college’s IRB.
At that point, several faculty members were contacted via e-mail asking permission to
present this study to their classes. Responses came randomly over a 3-month period
giving options of times and dates that would be convenient for the instructor. With
confirmed schedules, I proceeded to acquaint these classes with my research at the
beginning of each class period, explaining the purpose, and procedure of data collection.
The presentation took approximately 15 minutes depending on the number of questions
posed by the students. Potential participants expressing interest in the survey were given
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a consent form, detailing participation requirements; an objective extraversion survey,
where they rated an instructor thought of as skillful; a Barsch Learning Style Inventory,
where they answered questions about their learning preferences; and a demographic
questionnaire with the understanding that participation was strictly voluntarily and there
would be no incentives or negative consequences for their involvement. A self –
addressed stamped envelope was also included so that the completed inventories could be
mailed to a specified post office box. A total of 600 inventories were given out to
students with a return rate of 56%, totaling 327 questionnaires over the span of
approximately 4 months from 18 classes. Subject areas for these classes consisted of
Psychology, Sociology, and Education. Although permission was eventually granted by a
second community college’s IRB to collect data, the timeliness of the research was
considered and an ample amount of inventories had already been received from the first
community college I approached, therefore inventories were never distributed to the
second college. Data were manually keyed into the SPSS system for analysis.
The sample data was reviewed for completeness with the initial number of study
participants totaling 327students.Out of the 327 inventories, 23 had missing demographic
information bringing the number of inventories down to 304 from the initial number of
327. Two individuals (Code ID #112 and Code ID #217) noted that they were
transgendered. These individuals were deleted from the dataset so that the variable
Gender could be constructed as a dichotomous indicator. This elimination reduced the
sample size of the dataset from 304 respondents to 302 respondents.
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Two respondents had missing data. Respondent Number 6 had two questions with
missing responses and Respondent Number 14 had one response that was missing. In
order to ensure that sample size remain above the critical threshold of 300, it was
determined that mean values would be calculated minus these missing values for these
two inventories. SPSS calculated the scale score (as an average item response) without
the missing item(s). Using this procedure allowed the dataset to remain at a sample size
of 302 respondents.
As can be seen in Table 1, the majority of respondents (71.2%) are between the ages
of 18 and 25. Less than 1% of respondents are over the age of 50. Table 2 also reveals
that the sample is roughly split between men (42.1%) and women (57.9%). Six out of
every 10 respondents (60.3%) are Hispanic, whereas one out of every four respondents
(23.8%) are White. Blacks comprise 13.6% of the sample, and the remaining 2.3% of the
sample is Asian.
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Table 1
Demographic Variables Used in the Statistical Analyses Frequency
Distribution of Age Gender and Race
Variable
Frequency
%
18-25
215
71.2
26-33
41
13.6
34-41
36
11.9
42-49
8
2.6
Over 50
2
0.7
Male
127
42.1
Female
175
57.9
White/Caucasian
72
23.8
Black/African American
41
13.6
Hispanic/Latino(a)
182
60.3
7
2.3
Age of respondent
Gender of respondent
Race of respondent
Asian American
Demographic statistics for San Antonio Community College sample reflect the
general population in the city of San Antonio. According to the United States Census
Bureau (2010) the Hispanic population in San Antonio represents a majority of residents
at 63.2% while those reporting as White with no Hispanic lineage is at 26.6%. Blacks
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represent 6.9% of the population, which is considerably less than found in this study
while Asians are at 2.4%. Similarly, the racial/ethnic percentage in this research
described participants as 60.3 % Hispanic, 23.8 % White, 13.6 % Black and 2.3% Asian.
The United States Census reports approximately 51.2% of San Antonio residents as
female, while 57.9% are female in the study. However, the variable of age was dissimilar
in this study to city and state statistics due to the fact that younger people are more apt to
attend community colleges than older adults.
At San Antonio Community College, where this study was conducted 71.2% of
respondents were between the ages of 18 and 25, 13.6% between the ages of 26 and 33,
11.9 % between the ages of 42 and 49 while only 2% of participants were over 50.
According to the American Association of Community Colleges, (2014) the age
distribution of this sample does reflect community colleges throughout the United States.
It has been reported that the mean age of a community college student in the United
States is 24, while 57% of the community college population are between the ages of 2239 and only 14% are over the age of 40. In addition, gender for the community college
student nationwide is at 57% female, which is the same gender percentage as in this
study. It is concluded that demographic results are in agreement with local, state and
federal statistics for this region of the country. Therefore the sample in this study is a true
representation of the San Antonio population regarding race/ethnicity and a true
representation of community colleges regarding age and gender.
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Research Questions and Variables Used
The study seeks to determine if a relationship exists between the processes in which
an individual learns (auditory, visual, or kinesthetic) and the degree of extraversion
permeated in the instructor. In order to answer this question, the following hypotheses
were created:
1. H0: There is no relationship between teacher extraversion and a student’s
H1: There is a relationship between teacher extraversion and a student’s dominant
learning style.
2. H0: There is no relationship between teacher extraversion and visual learning style
scores.
H1: There is a relationship between teacher extraversion and visual learning style
scores.
3. H0: There is no relationship between teacher extraversion and auditory learning
style scores.
H1: There is a relationship between teacher extraversion and auditory learning
style scores.
4. H0: There is no relationship between teacher extraversion and kinesthetic learning
style scores.
H1: There is a relationship between teacher extraversion and kinesthetic learning
style scores.
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For all of the four null and alternative research hypothesis sets above, four of the five
variables (BFI – Extraversion; BLSI – Visual; BLSI – Auditory; BLSI – Kinesthetic) were
measured as a continuous variable. Dominant Learning Style was measured as a
categorical variable. A respondent was placed into one of the three learning style
categories according to the highest score received from the three learning style
categories. Even if scores were close, the dominant learning style was identified from the
highest value.
Consequently, all of the research hypotheses above sought to investigate whether or
not a relationship existed between the variable “instructor extraversion” and a
respondent’s visual, auditory, kinesthetic, and dominant learning style. A One-way
Analysis of Variance (ANOVA) was used to see if an instructor’s extraversion score
varied as a function of a respondent’s dominant learning style. According to Lesser and
Melgoza (2007), the ANOVA is used to determine whether there are any significant
variations between the means of three or more groups. An ANOVA was used to
investigate Hypothesis 1. Hypotheses 2 through 4 were investigated via a series of
Pearson correlations. Pearson’s correlation coefficient technique is the optimal approach
for investigating hypotheses 2 through 4. As Ritchey (2008) noted, correlation is the
correct method to use when one wishes to see if a relationship exists between two
variables. Ritchey further noted that correlation analysis requires that both variables be
measured at either an interval or ratio level (i.e., a continuous level), a condition that is
satisfied in the current analysis scenario. As such, a Pearson’s correlation was used as the
analysis technique to investigate the tenets of research hypotheses 2 through 4.
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Three additional analyses were conducted to see if there were differences in any of
the four key variables (BFI – Extraversion; BLSI – Visual; BLSI – Auditory; BLSI –
Kinesthetic) as a function of the three demographic variables of gender, age and race. In
order to determine if there was a difference in the four key variables as a function of a
respondent’s age, a Spearman’s rho correlation coefficient technique was used. Because
the three key variables are continuous in nature, and because the variable Age was
modeled on continuous data but was operationalized as an ordinal variable, a Spearman’s
rho correlation is the appropriate technique (Ritchey, 2008). In order to determine if there
was a difference in the four key variables as a function of a respondent’s gender, an
independent sample t test was used. Given the continuous nature of the three key
variables and the dichotomous nature of the variable Gender, the use of the independent
samples t-test is appropriate (Ritchey, 2008).
Finally, because the variable Race is a multiple category nominal-level variable, and
because each of the three key variables are continuous, ANOVA is the appropriate
analysis technique in this situation. As Ritchey (2008) notes, ANOVA demands a
continuous outcome variable and a factor variable that is discrete in nature and has more
than two categories.
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Descriptive Statistics
Table 2
Means and Standard Deviations, Focal Variables
Variable
Mean
Std. Dev.
BFI – Extraversion
28.11
4.31
BLSI – Visual
3.65
0.60
BLSI – Auditory
3.30
0.69
BLSI – Kinesthetic
3.15
0.63
Table 2 presents information on the four focal variables that were used in the
analysis. The first variable in the table, BFI – Extraversion, represents a respondent’s
observations about a particular instructor’s level of extraversion. It poses the question of
whether or not the instructor, chosen by the respondent, was viewed as an extravert. The
mean score for the extraversion scale is 28.11. Possible values for mean scores are
between 8 (true introverts) and 40 (true extraverts), which implies that students view
instructors as having a proclivity to the extraversion characteristic.
The next three variables in Table 2 indicate the average level of visual,
auditory and kinesthetic learning style among respondents. Among the 302 respondents,
it appears that levels of visual learning (M = 3.65, SD = .60) are higher than are levels of
auditory learning (M = 3.30, SD = .69) and kinesthetic learning (M = 3.15, SD =.63).
Indeed, it appears that among respondents, a visual learning style is the preferred method
through which to learn.
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Cronbach Alpha Reliability Estimation
Table 3
Internal Consistency Values (Cronbach α)
Scale
BFI – Extraversion
BLSI – Visual
BLSI – Auditory
BLSI – Kinesthetic
α
0.73
0.40
0.54
0.36
Table 3 presents the Cronbach’s alpha reliability coefficients for each of
the four scales that were used in the current investigation. As Tavakol and Dennick
(2011) noted, the alpha statistic was developed by Cronbach to provide a measure of the
internal consistency reliability of a scale. The measure of alpha ranges between a value of
0 and 1, with higher scores indicating better reliability. Scores of .70 or higher suggest
that a scale has an acceptable level of reliability (Cronbach, 1970), although lower levels
of alpha are also seen as reliable when a scale has only a few items (Tavakol & Dennick,
2011). Of the four scales presented above, only the BFI – Extraversion scale
demonstrates acceptable reliability, although the BLSI – Auditory scale does approach
the level of acceptability. Both the BLSI – Visual and BLSI – Kinesthetic scales have low
reliability scores.
Cronbach’s scores were examined after removing some questions presenting low
item total correlations. The auditory scale, comprised of eight items as examined after
removing L5 and L8; variable L9 was removed from the kinesthetic scales, and variables
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L16 and L20 were removed from the visual scales to achieve an optimal Cronbach’s
alpha reliability. However, the increase in Cronbach’s alpha were minimal and
consequently, this procedure was abandoned.
In analyzing the variable of age and its relation to learning modalities and
preference of extraversion, a Spearman rho correlation was conducted and results are
examined in Table 4.
Table 4
Spearman Correlations: Age
and Learning Style
Variable
BLSI - Visual
BLSI - Auditory
BLSI - Kinesthetic
Age
r
p
0.11
0.06
0.17
0.00
-0.07
0.24
Table 4 contains the statistical results for the correlation of the variable Age with
the four key variables or BFI – Extraversion, BLSI – Visual, BLSI – Auditory, and BLSI –
Kinesthetic. As can be seen in Table 4, age is positively correlated with extraversion and
positively correlated with an auditory learning style. The Spearman rho correlation results
contained in Table 4 suggest that as students get older, they prefer extraverted instructors
and are more likely to report an auditory learning style.
Table 5 contains the results of the independent sample t-test results to determine if the
average scores of the three key variables will differ as a function of a respondent’s
gender. As can be seen in Table 5, there are no statistically significant differences in any
of the three variables as a function of a respondent’s gender.
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Table 5
Independent Samples t-test for Gender Difference in Learning Style
Variable
BLSI - Visual
BLSI - Auditory
BLSI - Kinesthetic
Male
Mean
SD
3.65
0.58
3.38
0.62
3.15
0.71
Female
Mean
SD
3.64
0.62
3.25
0.74
3.14
0.57
t
0.23
1.61
0.14
p
0.11
0.89
0.81
Note: n=302
Table 6
One-way Analysis of Variance (ANOVA) for Race/Ethnicity Difference in Learning Style
Variable
BLSI - Visual
BLSI - Auditory
BLSI - Kinesthetic
White
Mean
SD
3.59
0.64
3.30
0.64
3.25
0.69
Black
Mean
SD
3.55
0.52
3.13
0.68
2.80
0.70
Hispanic
Mean
SD
3.70
0.61
3.36
0.72
3.20
0.57
Asian
Mean
SD
3.32
0.35
3.00
0.29
2.68
0.28
F
1.699
1.735
6.705
Note: White n=72; Black n=41; Hispanic n=182; Asian n=7.
Table 6 above presents the results of the one-way ANOVA to determine if the three
key variables will differ as a function of a respondent’s race. As can be seen in Table 6, a
respondent’s kinesthetic learning style will indeed vary as a function of race. Post-hoc
analyses reveal that with respect to a kinesthetic learning style, Asians (M = 2.68) are less
likely to use this learning style than Whites (M = 3.25), Blacks (M = 2.80) or Hispanics
(M = 3.20).
p
0.16
0.00
0.66
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Hypothesis 1: Statistical Results
Table 7
One-way Analysis of Variance (ANOVA) Results, Hypothesis 1 Test
Variable
Visual
Mean
SD
Auditory
Mean
SD
Kinesthetic
Mean
SD
BFI - Extraversion
28.74
27.60
27.00
4.15
4.49
4.18
F
p
4.079
0.02
Note. Visual n = 161; Auditory n = 92; Kinesthetic n = 49.
Table 7 shows the results of the one-way ANOVA that was used to investigate the
first hypothesis. As can be seen in Table 4, a respondent’s perceived level of instructor
extraversion will indeed vary as a function of the student’s dominant learning style (F
(2,299)= 4.079, p = .02). Post-hoc analyses via a Tukey’s HSD test reveal that with
respect to learning style, visual learners (M = 28.74; p = .03) are more likely to prefer an
extraverted instructor as compared to kinesthetic learners (M = 27.00). The results of the
ANOVA provide support for the tenets of Hypothesis 1 that there is a relationship
between teacher extraversion and a student’s dominant learning style. For hypothesis 1,
we can reject the null hypothesis and conclude that extraversion will vary as a function of
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Hypothesis 2 through 4: Statistical Results
Table 8
Pearson Correlations between teacher extraversion and student learning style
r
p
BLSI – Visual
-0.03
.557
BLSI – Auditory
-0.19
.001
BLSI - Kinesthetic
-0.12
.038
Note: n=302
Table 8 presents Pearson correlations for all four of the focal variables used in this
investigation. As can be seen in Table 8, there is no correlation between extraversion and
visual variables. However, there are statistically significant negative correlations between
the trait of extraversion and an auditory or kinesthetic learning style. The negative nature
of the relationships suggests that students who have relatively high scores on the auditory
or kinesthetic scales, tended to rate their favorite teacher as relatively low on the
extraversion scale.
Summary
In summary, the statistical results in Table 7 concludes support for hypothesis 1.
An instructor’s level of extraversion does influence a student’s propensity to learn
according to a dominant learning style. Table 8 provides only partial support for
hypotheses 2 through 4. There is no support for Hypothesis 2 (that there would be a
relationship between teacher extraversion and visual learning style scores) from the data.
For Hypothesis 2, I would fail to reject the null hypothesis and find no support for the
alternative hypothesis. However, both Hypothesis 3 (that there would be a relationship
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between teacher extraversion and auditory learning style scores) and Hypothesis 4 (that
there would be a relationship between teacher extraversion and kinesthetic learning style
scores) are supported by the data. For these hypotheses, I can reject the null hypothesis
and conclude that as an instructor’s extraversion increases, a student with an auditory or
kinesthetic learning style is less likely to appreciate the teaching style/mannerisms of the
instructor. In Chapter 5 I expound on the ramifications and associations of these results.
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Chapter 5: Discussion, Conclusions, and Recommendations
Introduction
This chapter addresses conclusions, implications, and recommendations that have
resulted from this study’s research questions. A quantitative correlational study was
conducted to examine relationships between an instructor’s degree of extraversion and a
student’s learning modality of visual, auditory, or kinesthetic learning. Instructor
extraversion was measured using the extraversion portion of the BFI (John, Donahue, &
Kentle, 1991). Students in psychology, sociology, and educational courses at a southwest
community college were asked to rate an instructor. This instructor, from the student’s
viewpoint, was one who conveyed information successfully and basically taught well.
They were also asked to complete a BLSI (Barsch, 1996) and a demographic
questionnaire (U.S Census, 2010). The BLSI, consisting of 24 questions, rated students
on three learning modalities widely used to determine learning strengths and preferences
in auditory, visual and kinesthetic sensory receivers. The demographic questionnaire
distributed to participants contained gender, age and racial origin queries to examine
correlations between these entities and learning style modalities. A total of 600
inventories were distributed through community college classrooms with 327 inventories
collected; 25 were deemed unusable, resulting in a final count of 302 inventories
involved in this study.
In this chapter, a summary of the research is presented; findings on demographic data
and Research Questions 1 through 4 are examined and interpreted, relating results to
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Chapters 1 and 2 respectively. I re-emphasize postulates stated previously in
corroborating and supporting conclusions derived from the data. Discussed in depth are
implications and recommendations for social change, actions proposed, and future
research. Finally, the significance of this research is recognized along with a concluding
synopsis.
Interpretation of Findings
Out of a total of 302 inventories, 161 individuals were identified as visual learners,
92 identified as auditory learners and 49 participants were categorized as kinesthetic
learners. The questions interpreting learning styles were from the Barsch Learning Style
Inventory (Barsch, 1996). The queries for observer rating extraversion were taken from
the Big Five Inventory which resulted in an alpha level of .730, acceptable range.
Cronbach’s alpha values were 0.399 for visual, 0.536 for auditory, and 0.359 for
kinesthetic. Kratzig and Arbuthnott (2006) stated that the BLSI had modest reliability,
reporting Cronbach’s alpha as 0.54 for visual and 0.56 for auditory in their analysis.
Reliability of a study conducted by Hansen and Cottrell (2012) of the BSLI was also
comparable to this study, noting values for Cronbach’s alpha at .56 for auditory and .27
for visual learning styles. A total of eight items per scale was administered.
Research Question 1
Research question 1 asked if there is a relationship between an instructor’s level of
extraversion and a student’s dominant learning style. The results indicated a correlation
between instructor extraversion and a visual learning style (p < .05), which is to say that
students with a propensity to learn visually prefer extraverted instructors, more so than
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auditory or kinesthetic learners. Therefore, there is support for the alternative hypothesis
that a student’s dominant learning style is interrelated with an instructor’s level of
extraversion. The null hypothesis is rejected and the alternative hypothesis is supported.
Although I speculated that the auditory learner, with characteristics of listening skills,
would be the learning style most benefiting from an instructor’s high degree of
extraversion, my conjecture was not the case. Mean differences are significant, however
slight (n2 = 0.03), and the evidence suggests that a learner who likes to learn visually will
be inclined to prefer an instructor with a higher degree of extraversion over an auditory or
kinesthetic learner. Participants were asked to rate an instructor they thought taught well,
not one they necessarily liked. Visual learners expressed a preference to learn from an
instructor that was more of an extravert than not. Several studies have indicated that
range of motion and expressive gestures are positively correlated with extraversion
(Argyle, 1988; Brebner, 1985; Gallaher, 1992). The visual effect that an extraverted
instructor might have on a visual student’s attentiveness is noteworthy.
Explanations for these results could originate from the demographics of the San
Antonio area, with a large population of second language learners (United States Census
Bureau, n.d.). According to Gilakjani (2011), second language learners are prone to
visual cues and instructions. The large Hispanic population (53%) at the community
college might have assisted in the evidence pointing towards visual learners as the
primary correlational variable to extraverted instructors. As stated in Chapter 1,
instructors who were less serious in their teaching and research were more likely to be
extraverts (Friedman, Förster, and Denzler, 2007). For many community college
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instructors, teaching courses is a secondary vocation after retirement or in conjunction
with another occupation (Modern Language Association Committee on Community
Colleges, 2006), implying that a large percentage of these instructors are extraverts,
resulting in a disproportionate extraverted faculty. This assertion is supported through a
normative sample by Srivastava, John, Gosling, and Potter (2003) where they reported
extraversion mean scores of 3.12 to 3.31 and standard deviations of .85 to .92 depending
on age. This study’s report of mean scores of 4.02 and standard deviations of .62 suggests
that student choices have been limited to a preponderance of extraverted instructors.
Research Question 2
Is there a relationship between instructor level of extraversion and a visual learning
style? Results indicate that there is not support for the alternative hypothesis and the null
hypothesis should not be rejected. Failure to accept the alternative hypothesis presents
various conjectures. Dobson (2010) pointed out that most college undergraduates
perceive themselves as visual learners. In the current study, 161 or 53.3% of the 302
participants identified as visual learners. However, while hypothesis 1 supports a closer
relationship with instructor extraversion to the visual learner than the auditory or
kinesthetic learner, it has failed to confirm that visual learners profit from having an
extraverted instructor.
Horton, Wiederman, and Saint, (2012), state that while attending lectures is weakly
correlated to academic performance, it is unclear if attending lectures is beneficial to any
particular learning style. However, they do provide evidence that furnishing materials
such as power points, lecture notes and video recordings in lieu of attending lectures
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proves to be more beneficial to all learners. Perhaps the extraverted instructors, chosen as
effective teachers, did include various visuals in their teaching practices or were intensely
dramatic in the use of descriptive words and examples, attending to the visual learners
needs. Contrastingly, this technique was possibly neutralized by a continuous droning of
words and long winded sentences. Or perhaps visual learners are taking notes, drawing
pictures or performing activities to visually imprint concepts while the instructor is
speaking, being able to focus visually and grasp onto certain ideas, while missing parts
of the over stimulating verbal lecture/discussion. Reddy (2013) states that visual learners
gravitate towards the written word and will diligently write down every word. Although
there is no support between the visual learner and the extraverted instructor for
hypothesis 2, hypothesis 1 does show more of a positive connection than either the
auditory or kinesthetic learner.
Research Question 3
Research question 3 inquired whether there is support for a relationship between
teacher extraversion and an auditory learning style. The evidence suggest there is a
negative relationship. Confidently, I speculated that a positive correlation would be
apparent. Reiterating from chapter 2, auditory learners have astute listening skills (Dunn
& Honigsfeld, 2009) and would therefore seem to be attentive to the extraverted
instructor’s every word. Additionally, the consensus is that auditory learners have
outgoing personalities and enjoy talking (Vincent, A., & Ross, D. (2001). They learn best
by listening, but also by repeating what they have learned and verbally internalizing what
they have learned. Dialogue between instructor and student, or student and student, may
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be essential for the auditory learner to process and understand information (Vincent and
Ross, 2001). If an extraverted instructor’s lecture does not permit verbal interaction then
the auditory learner may lose interest in the learning process. Granted, extraverted
instructors should welcome questions and lively debates, but if prone to lecture for long
periods without interruption, monopolizing verbal communication, relishing in the sound
of their own voice, the auditory student may become disengaged.
This negative relationship implies that an introverted instructor’s mannerisms may be
agreeable to the auditory learner, where the introverted instructor is a facilitator who
guides interactions but is willing, if not offering, to limit unessential comments and
verbal guidance. This leaves the auditory student with ample opportunity to ingrain
information by restating the instructor’s words, asking questions, making comments and
partaking in dialogue about the concept or topic. Without the auditory student’s active
involvement, optimal learning may not occur. They learn by participating in
conversations and expressing their own ideas (Vincent and Ross, 2001). Activities that
engage the auditory learner, like group conversations, could take precedence over
listening to an extraverted instructor, who monopolizes the conversation.
Research Question 4
Regarding hypothesis 4 of whether a correlation exists between instructor degree of
extraversion and a kinesthetic learning style, there is a negative correlation. Kinesthetic
learners are poor listeners (Vincent and Ross, 2001) and thereby may become bored or
non-responsive to an instructor with a high degree of extraversion and talkativeness.
They learn by doing more so than listening. According to Beagley (2011), kinesthetic
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learners process tactile information effortlessly. They may become restless during
lectures and have trouble focusing. The negative relationship between extraverted
instructors and kinesthetic learners may relegate itself to the same difficulties as the
auditory learner, where the instructor lectures continuously and does not provide
opportunities for group or individual presentations, experimentation or role playing. As
stated in chapter 1, dominance is an indicator of extraversion (Goldberg, 1993; Wiggins,
1992) and in conjunction with the expected leadership role of the instructor, a kinesthetic
learner may be unresponsive to an extravert’s techniques.
Moreover, opportunities for enhancing the kinesthetic student’s learning style may
not be presented in a community college setting. Mobley and Fisher, (2014) contended
college classes are geared towards lectures and note taking. They have offered
alternatives to instruction practices in the form of students physically moving around the
classroom in favor of a particular viewpoint, and partial ownership of the classroom
blackboard. The assertion is that instructors should use kinesthetic learning principles on
a continual basis. It would seem that instructor’s possessing the characteristic of
extraversion would gladly fulfill this need if allowed to do so by university
administration. Eddy, (2010) addressed the imperative need for change among
community college administration by recognizing the importance of culture,
collaboration and the implementation of contemporary methods of teaching.
Age
A Pearson correlation on age and the three learning style variables implied that
older participants were more likely to rate their preferred instructor high in extraversion
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and that they had a tendency towards higher scores on the auditory learning subscale than
their younger counterparts (p <.01). A study conducted by Kishon-Rabin, Avivi-Reich
and Ari-Even Roth (2013) support the results of this study that some characteristics of
auditory learning may be maintained in older adults. History suggests that as age
increases, various sensory channels may decrease such as sight, hearing and physical
movement. These results are for consideration, at best, since the number of participants
over the age of 41 was negligible (3%).
Gender
As in many studies (Slater, Lujan, and DiCarlo, 2013; Shah, Ahmed, Shenoy, and
Srikant, 2013), gender in this study had no significant effect on learning style
preferences. In fact, both of the above mentioned studies determined that a multi-modal
learning style was preferred by both male and female students. Findings in this
examination indicate there is no specific preference of learning style by gender. This is
substantiated by research conducted by Jones, Reichard and Mokhtari (2003), where
findings indicate there are no statistically significant differences in any of the three
variables of learning styles as a function of a respondent’s gender.
Race
With regards to this study, data analysis established that kinesthetic learning style does
differ with regards to race (p < .01). Hispanics are more prone to a visual learning style
than other races/ethnicities. Blacks are less likely to use a kinesthetic learning style than
Hispanics or Whites. Asians are less likely to be kinesthetic learners than Whites,
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Hispanics or Blacks. Results are significant although sample size of Asian participants
was low (2.3%).
Previous studies have indicated that English Language Learner (EFL) students have a
tendency towards kinesthetic learning styles (Peacock, 2001; Dunn, Griggs, and Price
1993). While Boyking and Cunningham (2001) published results indicating that
incorporating music and movement into teaching strategies of Black students proved to
be beneficial in learning. Contrastingly, many more studies advocate the variability of
learning styles among cultural groups taking into account the experiences, skills and
interests of an individual student from a particular culture (Gutiérrez and Rogoff, 2003).
Methodological, Theoretical and Empirical Implications
Implications of these findings suggest there is no universal technique of good
teaching. However, there is some support for substantiating a system of instructor level of
extraversion to a particular learning style of a student. Conceivably, it could be beneficial
to focus our attentions elsewhere in the world of pedagogical relationships. Perhaps it is
the technique and not the personality of the teacher that drives student learning. There are
an abundance of variables that effect student learning and instructor teaching. Whether it
is auditory, visual, or tactile, an instructor may be able to accommodate one learning style
over another, partly due to personable attributes and/or detriments. An educator’s ability
to connect with students on various levels is determined by the qualities and impairments
of both teacher and student. An ideal teachable moment is when a student grasps an idea,
concept, or fact that entices him/her to ponder further, make connections, and originate
new ideas. Although the educator’s role in facilitating these student epiphanies consists
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of training and skill, innate characteristics may enhance or detract from the learning
experience. Surely concessions should be attempted by both parties to produce the best
possible outcome, and yet, to compromise suggests a relinquishment of valuable
components that enhance the learning environment for both teacher and student.
The learner may abandon a successfully proven method of learning, opting for a
method influenced by an instructor’s natural inclinations of teaching. The instructor, on
the other hand, may be taken out of his/her comfort zone by having to present in a way
that feels unnatural or goes against his/her instinctive style of teaching. Either way,
energy is needlessly expended on necessary adjustments to instruction, instead of
grasping and dispensing information through inherent and familiar systems. Admittedly,
there are instances where instructor/learner differences can be altered, but oftentimes,
these differences cannot be modified. Binoy’s (2012) study conducted with monozygotic
twins using the VARK model revealed that a significant difference of learning styles was
found to hold true regardless of genetic sameness. The reality of multiple determinants
leads to an interpretation that an exact match between instructor and student is unlikely.
However, the results of this study encourages further assessment of key variables
effecting student instruction.
Implications for Social Change
Some studies have indicated that students are flexible in their learning styles and
can adjust to the teaching style of the instructor (Uğur, Akkoyunlu and Kurbanoğlu,
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2011). Other studies proposed that students recognize different learning strategies are
vital for various learning environments and students are able to adapt to instructor,
subject matter, or presentation style in which a topic is taught (Jones, Reichard and
Mokhtari, 2003). The implications of these assertions recognize the need for different
learning environments and that a cookie cutter approach to learning is obsolete.
Therefore, a society’s willingness to oblige learners and instructors must be flexible. The
necessity for unconventional learning environments is apparent.
Accepting and respecting alternative ways of teaching and learning should be at the
forefront of society’s agenda. An unbiased approach to pedagogical methods, the place
where learning occurs, and the instructor’s degrees or knowledge should not take
precedence over the information and skill that the learner has acquired. A prestigious
university should not be thought of as producing better students. When they are thought
of in this way, opportunities are given and doors are suddenly open for a chosen few,
disregarding those who attended less prestigious universities, but have attained great skill
and knowledge through an exceptional pairing between instructor and student.
Instructors may be well qualified on the subject matter and yet unable to convey
knowledge due to the instructor’s skill at teaching, or types of learners in the class.
Rather, a university’s merit should arise from the number of competent, well trained
graduates it produces, whether it is through on line-classes or brick and mortar
institutions. The distinction should be placed in a university’s ability to provide different
types of learning experiences. In this way, learners will truly feel they got their money’s
worth and that learning is a thorough and valuable experience.
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Recommendations for Practice
Institutions must do a better job of keeping students in school, however addressing
every student’s learning style becomes a time-consuming challenge. Precious time may
be lost, that could have been used in developing subject matter as opposed to making sure
everyone grasps an idea. Furthermore, the material, concept, or idea may go astray when
justifying individualized learning styles. The efficiency and clarity in which an instructor
can teach students, if preferences and inclinations are acknowledged, should be apparent.
If the instructor would teach the way in which his/her personality dictates, the student
who is inclined to excel with the right presentation style could flourish, and therefore, the
learning experience, instructor experience, and the dynamics of the institution should
reveal positive results. The capability of the instructor would be enhanced, because
he/she is in his/her comfort zone of teaching. Likewise, students thrive in the best
possible environment.
This proposal could fit many different classroom settings, from large lecture halls
to small classes of 15 or 20, where students are aware that classes would be administered
visually, with films and power points, or by auditory means, with lecturers and speakers,
or kinesthetically, with hands-on scenarios. Accommodating students by appealing to
their learning style is crucial toward societal gains. The results can produce a more
intelligent and informed workforce, while ensuring the survival of academic progress. To
implement a match between instructor and student, countless studies must be conducted.
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When these studies are eventually completed and a consensus formed, correct
prescriptions for learning will be available for the majority of the student body.
Recommendations for Further Study
Additional analysis of correlations between instructor extraversion and learning style
modalities are recommended, along with a suggestion to perform correlational studies of
the other Big 4 personality traits (openness, conscientiousness, neuroticism and
agreeableness) with the three learning style modalities. There are a plethora of variables
that effect student learning and instructor teaching. These variables must be considered
together, separately, and in conjunction with other factors. If there is a formula or
algorithm for correct teaching to a specific population, it is a complex abundance of
external and internal factors. It could be prescriptive per individual learner or groups of
learners and may also change over time. Implications of these findings suggest there is no
universal technique of good teaching. Consequently, exploring all possible factors is
necessary to gain insight into instructor/student paradigms. In addition, examining
relationships between students’ learning styles and their own level of extraversion may
prove to be significant, as well as the investigation into instructors’ level of extraversion
and style/skill in teaching are taken under consideration. Other questions concerning the
relationships between extraverted instructors/students and introverted instructors/students
deserves exploration.
Sun’s (2012) suggestion of an investigation into the incompatibility of
student/teacher relationships has weight. Salehi (2010) advised that future studies should
deliberate on personality factors of students and teachers; while Harris and Sass (2010)
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asserted that more than anything else, teachers significantly influence student
achievement, but the difference in teacher productivity is baffling. Combinations of
variables need investigation to compare with studies previously conducted. Terregrossa,
Englander, Zhaobo, and Wielkopolski (2012) contended that learning styles may differ
according to subject area, all other variables remaining constant. Studies have also
concluded that extraverted students preferred teachers of a witty nature to other teachers,
while introverted students preferred teachers who accepted the ideas of students and of
other teachers, however introverted students preferred teachers who had flexible
behaviors over other teachers (Akbar, 2009).
Investigating the compatibility of introverts and extraverts concerning teachers
and students is warranted. Research should inquire into whether there are any correlations
between student extraversion and learning modality preferences. Exploring whether a
learning style preference points to a student’s comfort while learning or his ability to
absorb information is another direction for study. Other studies could query as to the
extent learning style preferences are effected by cultural, ethnic or environmental
backgrounds and what is the nature of these dependences. More research is needed on the
extent that teaching to a particular learning style brings satisfaction to the learner and is
effective teaching, or is lacking in some way.
Investigations into an instructor’s skill at teaching to one learning style over
another warrants attention. In addition, exploring the extent that teaching practices
contribute to academic performance or the drop-out rate of community college students
has merit. What happens when students are given the choice of ways in which to learn?
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Can instructional technology be tailored to fit a particular style of learning? What are
some interventions that take learning styles under consideration and how effective are
these interventions? Does a mixture of learning styles in group work result in more
knowledgeable learners or can it hinder learning, and what combinations of learners
should be incorporated into groups? Is there an increase in conflict when learning styles
are mixed in these groups? And if there is conflict, then the question of whether or not
productivity increases in spite of this conflict arises. Perhaps making team members
aware of individual learning styles in a group reduces this conflict.
Conclusion
In summarizing the results, I have concluded that instructor extraversion is
conducive to a particular dominant learning style: visual. While there is a negative
correlation between auditory and kinesthetic learning style and level of instructor
extraversion, there is no significant correlation between the visual learning style and
degree of instructor extraversion. Thus, while visual learners scored their favorite
teachers higher on extraversion, an examination of the correlations between learning style
scores and teacher extraversion suggests this is due to the negative correlations with
auditory and kinesthetic styles rather than a positive correlation with visual style. While
visual learners are more adherent to an extraverted instructor than the auditory and
kinesthetic learner, there is no evidence suggesting that visual learners benefit from an
extraverted instructor. This study’s results also identifies particular racial/ethnic groups
who are prone to be one type learning style over another. Hispanics are considered more
visual than other races/ethnicities while Asians are less likely to be
107
kinesthetic learners than other races/ethnicities. There is no significant difference of
learning styles with regards to gender, while older students tend to gravitate towards
auditory learning.
There exists an enormous amount of literature concerning learning styles. While the
Dunn and Dunn modal (Dunn, Griggs, Olson, Beasley, and Gorman, 1995) has been well
popularized among the pedagogical community, some say that it is the teacher’s own
learning style that drives the type of instruction incorporated into their classroom (StittGohdes, 2003). Others proclaim that if teachers change instruction to accommodate a
particular learning style, other students may suffer because of the deviation in instruction
(Harris and Sass, 2010). Producing a best fit between instructor and student may
alleviate the problem, however the variables involved in this prognosis are dubious and
inconclusive. The question of whether race, age, gender, environment, culture, biological
make-up, a particular style of learning, or a combination of these categories play a major
role in predicting the type of instruction that is best suited for a student is
overwhelmingly complicated.
This study has determined that instructor level of extraversion can influence the
type of learner that will be served best, but results can be problematic. One reason is due
to the other variables mentioned above. Padhye (2013) research contended that university
teachers who display a high rate of extraversion attain higher levels of effectiveness with
their students. This study substantiates Padhye’s claim if the dominant learning style is
visual, being the opposite case if learners have an auditory or kinesthetic
108
learning style. However, like this study, Padhye failed to incorporate all variables that
could manipulate the outcome.
Currently, students’ learning styles are intermingled throughout community
colleges and not taken under consideration when scheduling student courses. Therefore,
participants are not assigned to courses by learning styles and instructors are not assigned
to any particular group of students other than subject matter or student choice at the time
of registration. Brooks and Khandker, (2013) contended that students are self-sorting.
That is to say that a student will automatically pick a class or instructor they feel will best
serve them, but there are limitations in this process as well. Students may not be
acquainted with the subject matter or the professor that is teaching the required class.
There may be scheduling conflicts prohibiting the student from making the desired
choice.
This study’s results are not conclusive by any means. The conclusions found in this
study lead to more questions and the determination that many more studies should be
conducted. Obtaining the ultimate skill, training, and knowledge in exchange for time,
money, and anticipated success is a problematic endeavor. Educational institutions are
given tasks of producing qualified candidates, participating in research and innovative
practices, while maintaining financial solvency. Reasoning dictates that the organization
and corroboration of administrations, instructors, and students can result in an
institution’s success or decline. Therefore, steps taken in finding solutions to seemingly
minor annoyances may appear inconsequential to the larger goals of the university, and
yet inconveniences (why students are not responding to teaching methods), may prevent
109
an instructor from pursuing research or prevent students from continuing with their
studies (they are not understanding concepts or processes). These hindrances can prevent
an educational system from thriving in the most essential way of producing a qualified
workforce.
This research’s findings are supported by a study conducted by Katsioloudis and
Fantz, (2012) where although there was some dissimilarity within majors, the general
dominant learning style for engineering, industrial, and technology students was the
visual style. Furthermore research suggests that 60% of people believe themselves to be
visual learners, being one of the easier styles to accommodate on a larger scale (Johnson,
2011).
This is in contradiction to Neuhauser’s study concerning the face to face learning
environment verses online learning. It was found that there was no evidence supporting
learning preference or type as a good predictor of achievement in a face-to-face or on-line
teaching environment (2002). Consequently, visual stimuli may be demonstrated in
person or with technology to attract the visual learner. The supposition that expertise,
experience, training and skill can outweigh a teacher’s personality characteristics must be
considered.
While this study has concluded that there is a connection between instructor
extraversion and student learning style, Kneipp, Kelly, Biscoe, and Richard (2010) found
evidence that agreeableness was the only personality trait that correlated significantly
with student ratings of instructional quality. In addition, Patricka (2010) contended that
instructor personality was essential in determining positive student evaluations above
110
grades and perceived learning. This implies that if an instructor is likeable, they will
receive a positive evaluation whether or not the student received a good grade or has
learned anything from the class.
Recent research (Harris and Sass, 2010) consistently found that teacher
productivity is the most important factor in student learning and that it is the components
of intelligence, teaching skills and subject knowledge that increases teacher productivity.
Yet, there are those who assert that teaching is an innate skill and can neither be taught or
learned (Peirce and Martinez, 2012). This conclusion was reached after surveying
teachers who reported that they acquired teaching skills through training and practice.
Also included was reading books on pedagogy, observing classes, taking classes and
attending workshops. Korte and Lavin (2013) found the best teaching traits in instructors
were content/subject matter expertise, strong communication skills, approachability,
work (industry) experience and class preparedness. Out of these traits, approachability
and strong communication factors are most in line with an extraverted instructor, the
others being inconsequential to personality characteristics. While it is evident that
educators must stay current in their field of expertise, developing new methods of
teaching and evaluating learning, it is also evident that a teacher’s personality plays a role
in pedagogy practices even though the trait of extraversion may be of minor significance.
111
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Appendix A: Consent Form
CONSENT FORM
You are invited to take part in a research study about the relationship between instructor
degree of extraversion and student learning style. The researcher is inviting all enrolled
students at St. Phillips College or San Antonio College over the age of 18 years of age to
be in the study. This form is part of a process called “informed consent” to allow you to
understand this study before deciding whether to take part.
This study is being conducted by a researcher named Celeste Bazier, who is a doctoral
student at Walden University.
Background Information:
Corresponding teacher degree of extraversion to student preferred learning style may be
imperative in producing the best results for students and teachers alike. The potential
implications address the placement of teachers in a learning environment that is best
suited to a particular type of student with a particular learning style and conducive to the
needs of a specific group in optimizing achievement.
Procedures:
If you are 18 years of age (or older) and agree to be in this study, you will be asked to:

Complete the extraversion portion of the Big Five Extraversion Inventory on a
previous instructor and…

Complete a Barsch Learning Style Inventory

Complete a general questionnaire about myself- age, race/ethnicity, gender.
Voluntary Nature of the Study:
This study is voluntary. Everyone will respect your decision of whether or not you
choose to be in the study. No one at your community college will treat you differently if
you decide not to be in the study. If you decide to join the study now, you can still change
your mind later. You may stop at any time.
142
Risks and Benefits of Being in the Study:
Being in this type of study involves some risk of the minor discomforts that can be
encountered in daily life, such as minor fatigue, stress or lack of memory recall. Being in
this study would not pose risk to your safety or wellbeing.
The ability of the student to recognize instructor personality traits that are best suited for
their particular style of learning may be crucial to academic success. This match may
reduce dropout rate and encourage the pursuit of educational accomplishments by making
learning a more enjoyable and valuable experience.
Payment:
There is no compensation, monetary or otherwise, for participation in this study.
Privacy:
Any information you provide will be kept anonymous. The researcher would only know
the identity of the participant if the participant elected to know inventory scores through
email. The researcher will not use your personal information for any purposes outside of
this research project. Also, the researcher will not include your name or anything else that
could identify you in the study reports. Data will be kept secure in a locked file cabinet at
an undisclosed location. Data will be kept for a period of at least 5 years, as required by
the university.
Contacts and Questions:
You may ask any questions you have now. Or if you have questions later, you may
contact the researcher via celeste.bazier@waldenu.edu. If you want to talk privately
about your rights as a participant, you can call Dr. Leilani Endicott. She is the Walden
University representative who can discuss this with you. Her phone number is 612-3121210. Walden University’s approval number for this study is IRB will enter approval
number here and it expires on IRB will enter expiration date.
The researcher will give you a copy of this form to keep.
Statement of Consent:
I have read the above information and I feel I understand the study well enough to make a
decision about my involvement. I confirm that I am at least 18 years of age, and by
completing these surveys and inventories, I agree to participate in the study as described
in this consent form.
143
Appendix B
Big Five Inventory- Observer Rating Scale
Think of a recent instructor or high school teacher who you enjoyed learning from,
thought you learned a lot from them, and can still remember many ideas and concepts
that were grasped in their classroom environment. This instructor does not necessarily
have to be likable but rather, were they a good teacher, easily relaying information. Rate
this professor according to the scale below.
1
Disagree
Strongly
Talkative
Reserved
Full of energy
Enthusiastic
Quiet temperament
Assertive
Shy or inhibited
Outgoing or sociable
2
Disagree
a little
3
Neither agree
nor disagree
4
Agree
a little
5
Agree
strongly
144
Appendix C
Barsch Learning Style Inventory
Often Sometimes Seldom
1.
2.
3.
4.
5.
6.
Can remember more about a subject through
listening than reading.
Follow written directions better than oral
directions.
Like to write things down or take notes for a
visual review.
Bear down extremely hard with a pen or pencil
when writing.
Require explanations of diagrams, graphs or
visual directions.
Enjoy working with tools.
Are skillful with and enjoy developing and
making graphs and charts.
8. Can tell if sounds match when presented with
pairs of sounds.
9. Remember best by writing things down several
times.
10. Can understand and follow directions on maps.
7.
11. Do better at academic subjects by listening to
lectures and tapes.
12. Play with coins or keys in pocket.
13. Learn to spell better by repeating the letters out
loud than by writing the word on paper.
14. Can better understand a news article by reading
about it in the paper than by listening to radio.
15. Chew gum, smoke or snack during studies.
145
16. Feel the best way to remember is to picture it in
your head.
17. Learning spelling by “finger spelling” the words
18. Would rather listen to a good lecture or speech
than read about the same material in a book.
19. Are good at solving and working on jigsaw
puzzles and mazes.
20. Grip objects in hands during learning period.
21. Prefer listening to the news on the radio rather
than reading about it in a newspaper.
22. Obtain information on an interesting subject by
reading relevant materials.
23. Feel very comfortable touching others, hugging,
handshaking, etc.
24. Follow oral directions better than written ones.
Jeffrey Barsch developed this short questionnaire to determine an individual’s preferred
method of learning. Please answer the following questions by checking the appropriate
line after each statement about auditory, visual and tactile learners. Inquiries about results
may be addressed to celeste.bazier@waldenu.edu.
146
Appendix D
Demographic information- Please answer BOTH Question 2 about Hispanic origin and
Question 3 about race. For this study, Hispanic origins are not races.
1. Your Age__ Gender ____M__F
2. Are you Hispanic, Latino, or of Hispanic origin?
___No, not of Hispanic, Latino, or of Hispanic origin
___Yes, Mexican, Mexican American or Chicano
___Yes, Puerto Rican
___Yes, Cuban
___Yes, another Hispanic, Latino, or Spanish origin----Print origin below, for example,
Argentinian, Columbian, Dominican, Nicaraguan, Spaniard and so on.
________________________________________________
3. What is your race? Check one or more.
___White_
___Black, African American, or Negro
___American Indian or Alaskan Native- Print name or enrolled in principal tribe below
___Asian Indian
___ Japanese
___Native Hawaiian
___Chinese
___ Korean
___ Guamanian or Chamorro
___Filipino
___Vietnamese
___ Samoan
___Other Asian—Print race for example
___Some
____Other Pacific Islander- Print race
Hmong, Laotian, Thai
for example, Fijian, Tongan,
Pakistani, Cambodian,
and so on.
and so on.
other race ---Print race ____________________________________

An Analysis of Instructor Extraversion and Student Learning Style

Transcription

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