the Article - Educational Technology & Society

Chen, C.-H., & She, H.-C. (2012). The Impact of Recurrent On-line Synchronous Scientific Argumentation on Students'
Argumentation and Conceptual Change. Educational Technology & Society, 15 (1), 197–210.
The Impact of Recurrent On-line Synchronous Scientific Argumentation on
Students’ Argumentation and Conceptual Change
Chien-Hsien Chen and Hsiao-Ching She
Institute of Education, National Chiao-Tung University, Taiwan // ptm1122@gmail.com // hcshe@mail.nctu.edu.tw
ABSTRACT
This study reports the impact of Recurrent On-Line Synchronous Scientific Argumentation learning on 8th grade
students’ scientific argumentation ability and conceptual change involving physical science. The control group
(N=76) were recruited to receive conventional instruction whereas the experimental group (N=74) received the
Recurrent On-Line Synchronous Scientific Argumentation program for about 25 physical science class periods
of 45 minutes each, which is about one third of the physical science class periods in a semester. Results indicate
that the experimental group significantly outperformed the conventional group on the post-Physical Science
Conception Test and the Physical Science Dependent Argumentation Test. The quantity and quality of scientific
arguments that the experimental group’s students generated, in a series of pre- and post-argumentation
questions, all improved across the seven topics. In addition, the experimental group’s students successfully
constructed more correct conceptions from pre- to post-argumentation questions across the seven topics. This
clearly demonstrates that the experimental group’s students’ argumentation ability and conceptual change were
both facilitated through receiving the Recurrent On-Line Synchronous Scientific Argumentation program.
Keywords
Scientific Argumentation, Conceptual Change, On-line Synchronous argumentation, Physical science, Recurrent online learning, 8th grade students
Introduction
The need to educate our students and citizens about how we know and why we believe in the scientific worldview
has become increasingly important. It is no longer sufficient to merely deal with what we know (Driver et al., 1996;
Millar & Osborne, 1998). Osborne et al. (2004) further pointed out that such a shift requires a new focus on how
evidence is used in science for the construction of explanations, that is, on the arguments that form the links between
data and the theories that science has constructed. More specifically, the construction of arguments is a core
discursive activity of science (Osborne et al., 2004). Scientific discursive practices such as assessing alternatives,
weighing evidence, interpreting texts, and evaluating the potential validity of scientific claims are all seen as
essential components in constructing scientific arguments, which also are fundamental in the progress of scientific
knowledge (Latour, 1987). In short, argumentation is a collective cognitive development process which involves
using evidence to support or refute a particular claim, coordinating the claims with evidence to make an argument,
forming a judgment of scientific knowledge claims, and identifying reliable and consensual scientific knowledge.
Several studies show that educational support of argumentation may foster students’ argumentation ability (JiménezAleixandre, & Rodriguez, 2000; Kuhn et al., 1997) and improve scientific knowledge (Zohar & Nemet, 2002).
Most of the argumentation studies were conducted in the classroom for a very short period of time and were not able
to improve students’ argumentation efficiently. The authors feel that it is necessary to provide students with the
opportunity to argue effectively with recurrent opportunities and for a longer period of time in order to improve the
quality of their argumentation. Osborne et al. (2004) suggested that developing argumentation in a scientific context
is far more difficult than enabling argumentation in a socio-scientific context. Students generally considered physical
science to be difficult to learn. Though it is rather difficult to improve argumentation in a science context, we believe
it is important to provide students with the recurrent opportunity to learn and use argumentation in the context of
physical science.
The constructivist view of learning highlights the significance of the individual learner’s prior knowledge in
subsequent learning (Driver & Bell, 1986). Cobern (1993) shares the similar idea of learning as a process wherein an
individual is actively involved in linking new ideas with current ideas and experience. Learning by construction and
involving changes is similar to the idea that the construction of new knowledge takes place at a construction site
consisting of existing structures built on a foundation (Cobern, 1993). The notion of conceptual change involves the
restructuring of relationships among existing concepts and often requires the acquisition of entirely new concepts.
The students who learn something are the ones who understand a new idea, judge its truth value, judge its
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consistency with other ideas, and are willing to change their minds to accept it. It is recognized that learning does not
take place in a social vacuum (Driver, 1995). Driver (1995) indicated that whether or not an individual’s ideas are
affirmed and shared by others in classroom exchanges affects how the knowledge construction process is shaped.
The nature of argumentation has the potential to contribute to the collective development and judgment of scientific
knowledge claims and the identification of reliable and consensual descriptions of nature (Kolsto & Ratcliffe, 2008,
p.117). Much effort and many studies have focused on fostering students’ conceptual change from the constructivist
viewpoint (She, 2004; She & Lee, 2008; She & Liao, 2010; Hewson & Hewson, 1988; Venville & Treagust, 1998).
However, none of them have tried to include argumentation in fostering conceptual change.
Obviously, argumentation has great potential for fostering students’ communication skills in order to interchange
perspectives and meanings. Assessing alternatives, weighing evidence, interpreting texts, and evaluating the potential
validity of scientific claims are all seen as essential components in constructing scientific arguments. But how can
argumentation successfully foster students’ conceptual change? According to the previous conceptual change studies,
the following major characteristics are important for successful conceptual change: (1) Creating dissonance, which
can raise students’ awareness about their own conceptions and provide an opportunity for them to experience the
dissonance and become further dissatisfied with their own conceptions (She, 2004; Posner et al., 1982). (2)
Challenging students’ beliefs about science conceptions (She, 2004; Vosniadou & Brewer, 1987). (3) Providing
plausible mental structures for students to reconstruct more scientific conceptions (She, 2004). (4) Actively engaging
students in the process of conceptual change (Hewson & Hewson, 1983; She, 2004). (5) Actively involving students
in group discussions to shape their knowledge construction process and changing conceptions (Driver, 1995;
Venville & Treagust, 1998). Therefore, the ideas of successful conceptual change described above were taken into
consideration during our design of argumentation activity in order to optimize scientific learning.
Though there is a substantial body of research showing that instructors tend to adopt their conventional instruction
into online courses, however, Scagnoli, et al. (2009) suggested that simply changing face-to-face courses to an online
environment can’t confirm the same success. Additionally, consensus has not been reached regarding whether online learning is more effective than conventional instruction on students’ academic achievement. Many studies
suggest no difference in academic achievement scores following on-line learning and conventional courses (Delfino
& Persico, 2007; Russell, et al. 2009). Larson and Sung (2009) further demonstrated that there are no significant
differences on exam scores when comparing online, blended and face-to-face instruction. On the other hand, the
majority of articles reported that online learning is better than traditional learning with the focus on the perspectives
of engagement or social situations, pedagogical characteristics, and satisfaction (Larson & Sung, 2009; Menchaca,
2008; Wuensch et al., 2009) instead of focusing on students’ learning outcome. One study demonstrated that, for a
wellness course, the online learning group’s levels of achievement were significantly higher than those of the
traditional face-to-face learning group (Lim et al., 2008). Kirtman (2009) reported a contrary result that students who
received traditional instruction performed significantly better than the students who received online instruction, in
both mid-term and final exams. Salcedo (2010) further demonstrated that students who received traditional
instruction for foreign language classes performed better on three out of four assessments than did the students who
received online instruction. As the consensus still remains unclear, we are interested in exploring whether or not
students receiving the on-line scientific argumentation course perform better than the conventional group. From the
point of view of science educators, we claim that it is very difficult to bring about conceptual change and
argumentation unless the instructional design is based on well-developed conceptual change and argumentation
theories and models (Yeh & She, 2010). Though a few studies have proposed their on-line argumentative learning
environment for promoting students conceptual development and conceptual change (Ravenscroft, 2000, 2007), they
lack empirical evidences to prove their effectiveness. Thus, this study attempts to explore whether or not students
who received the On-Line Synchronous Scientific Argumentation learning would outperform a conventionally
educated group of students in their conceptual change and scientific argumentation.
Sandoval and Reiser (2004) suggest that online learning environments can provide excellent support for students
constructing their scientific explanations and knowledge negotiation process in argumentative writing. Synchronous
communication can deliver a higher degree of elaboration and construction of arguments as students work on a
common shared artifact (De Vries et al., 2002; Janssen et al., 2006). Our study specifically designed a synchronous
argumentation Web-based learning environment to provide students with the opportunity to argue with their group in
real time and to create a higher degree of elaboration and construction of arguments.
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Constructing a good argument is not a simple task and we believe that guidance and support would help students to
scaffold and build their sense of an effective argument. On-line argumentation provides the advantage of allowing
students to see arguments and counterarguments on the screen, which supports them in refining their argumentation
(Kirschner et al., 2003). Wray and Lewis (1997) have indicated that the use of “writing frames” would support the
process of writing and provide vital clues as to what is needed. Osborne et al. (2004) indicated that stems provide
students with prompts to construct their argument in a coherent manner and within a writing frame, which then can
be used as a structure for producing a written argument. Therefore, we specifically programmed our learning
environment to provide students with writing frames of five argumentation components to scaffold their arguments
in science learning.
The current study specifically designed On-Line Synchronous Scientific Argumentation learning to provide a
recurrent opportunity for middle school students to engage in argumentation for about one third of the physical
science class periods in a semester. The strategy is to provide students with writing frames of five argumentation
components to scaffold their arguments in the On-Line Synchronous Scientific Argumentation learning. We believe
that it is a promising direction, taking consideration of conceptual change aspects into the design of a series of pre-,
experiment-related, and post-argumentation activities.
Research Questions
Three major research questions were examined in the study in order to measure the effectiveness of On-Line
Synchronous Scientific Argumentation learning. The first question explored whether On-Line Synchronous
Scientific Argumentation learning was more effective than conventional instruction in facilitating students’
conceptual change as well as scientific argumentation in physical science. Second, examine the quantity and quality
of scientific arguments that experimental group’s students generated in a series of pre- and post-argumentation
questions across a semester. Third, explore the nature and extent of conceptual change from pre- to postargumentation question that the experimental group’s students made across a semester. In addition, the relationship
between scientific conceptual change and argumentation ability was examined.
Designs and Characteristics of the Recurrent On-Line Synchronous Scientific Argumentation learning
Recurrent On-Line Synchronous Scientific Argumentation learning is designed to provide recurrent argumentation
opportunities for students learning physical science, replacing the regular physical science in middle school.
Therefore, the five units of seven topics were chosen from the current middle school physical science mandatory
content and standards. The current study reported the effects of implementing seven topics for physical science:
chemical reaction (1 and 2), acid and base (1 and 2), oxidation and reduction, organic substances, and friction. Seven
topics of physical science were used in this study. Each unit generally covers two or three main topics, for instance
unit 1 on chemical reaction covers the influence of the contacting area on the rate of chemical reaction, and the
influence of concentration on the rate of chemical reaction. Each topic is specifically designed a pre-argumentation
question and an experiment-related argumentation question was focused on the core concepts of the preargumentation question that they argued (figure 1). Students were asked to provide reasons for the argument and
went to an actual laboratory to carry out their experiments based upon their hypothesis and experimental design. The
same post-argumentation question was given for students to argue again after finishing the laboratory work.
Facilitate students’ conceptual change
To facilitate students’ conceptual change, each topic is specifically designed to initiate a pre-argumentation question,
followed by an experiment-related argumentation question, the activity of carrying out the experiment in the
laboratory, and finally a post-argumentation question. Students would be exposed to different ideas which may be
different from their own during the pre-argumentation and experiment-related argumentation question. After they
carry out the experiment and receive the result from the experiment, dissonance is created and they build a plausible
mental structure if the result is different from their prediction. The same post-argumentation question is given for
students to argue again after finishing the laboratory work. Post-argumentation provides them an opportunity to
reconstruct their mental structure according to the experiments they have visualized, arguing with peers, exchanging
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conceptions, justifying their belief, and further modifying their original conceptions throughout the process. This
process is intended to encourage students to reconstruct their scientific conceptions through a series of preargumentation, question-testing argumentation questions, laboratory activities, and post-argumentation.
Facilitate students’ argumentation ability
In order to promote students’ argumentation ability, the Recurrent On-Line Synchronous Scientific Argumentation
learning environment has tools specifically designed for students to use while they are participating in
argumentation. In order to facilitate students’ ability to produce a good written argument, our interface specifically
designed two layers of templates for them to use. The first layer provides the definition and choices of five
components of argumentation: data, claim, warrant, backing, and rebuttal; the second layer provides three or four
writing frames for each component of argumentation (figure 2).
Figure 1. On-line pre-argumentation discourse and first layer of template
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The writing frame is intended to provide guidance and support that will help students in constructing a good
argument. The following stems were provided: “I think/believe…, because…; The reason why I agree
with…argument, is because the evidence of……; I do not agree with…my reason is…” Students need to choose one
of the components of argumentation first and then choose one from three or four writing frames that they feel
appropriate to share their argument. The learning environment provides the advantage of real time argumentation, so
students can receive prompt rebuttals to their arguments which can better retain their interest and thus make learning
more effective.
Figure 2. On-line post-argumentation discourses and second layer of template
Method
Participants and procedures
A total of 150 eighth grade students, recruited from four classes of a middle school, participated in this study. Two
classes of students (74) received the Recurrent On-Line Synchronous Scientific Argumentation learning
(experimental group) and the other two classes of students (76) received conventional instruction (control group).
The experimental group’s students were further divided into 12 groups, with an average of six students assigned to
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each group. The experimental group received the seven topics of the physical science Recurrent On-Line
Synchronous Scientific Argumentation learning for one semester, with 25 class periods, each class lasting about 45
minutes. This was about one third of the physical science class periods over a semester. The teacher introduced the
five components of argumentation to the students and used it in the classroom for one class before the students
received the Recurrent On-Line Synchronous Scientific Argumentation learning and assessment. The conventional
group students went through the same content of physical science in traditional instruction and traditional laboratory
work.
All students were administered the two-tier Physical Science Conception test (PSCT) and the Physical Science
Dependent Argumentation Test (PSDAT) before and one week after learning. In addition, the experimental group
students’ on-line scientific argumentation process also was collected to determine the quality and quantity of
students’ argumentation and scientific conceptions they held before and after learning from the OLSA.
Instruments
Physical Science Conception test (PSCT)
The PSCT is a two-tier multiple choice diagnostic instrument that was developed to measure the degree of students’
conceptual change in physical science conceptions. The content validity was established by the same panel of six
evaluators, ensuring that the items were properly constructed and relevant to the seven topics of physical science
Web-learning materials that we developed. There are five items for each topic, and each item contains two tiers. In
the first tier, students are required to choose the correct scientific concepts, while in the second tier they choose the
correct reason for choosing these specific concepts. There are 35 items and each item has two tiers. Students need to
answer both tiers of each question correctly in order to receive one point, so the highest possible score is 35. The
Cronbach α of ADRT was 0.86 for the pre-test and 0.92 for the post-test.
Physical Science Dependent Argumentation Test (PSDAT)
The PSDAT is a two-tier multiple choice diagnostic instrument that was developed to measure the degree of
students’ argumentation ability involving physical science conceptions. There are five scenarios, covering five units
of seven topics. Each scenario includes the contextual background and argumentation discourses. There are five
questions under each scenario, for a total of 25 questions. Each question contains two tiers. The first tier of each
question requires the student to identify a specific statement from the argumentation discourses at scenario as a
correct data, claim, warrant, backing, or rebuttal, respectively, and justify why they chose that specific statement as a
correct data, claim, warrant, backing or rebuttal. The content validity was established by the same panel of six
evaluators, ensuring that the items were properly constructed and relevant to the five units of the OLSA physical
science learning program. There are 25 items covering five units. Students need to answer both tiers correctly in
order to receive one point, so the highest possible score is 25. The Cronbach α of PSDAT was 0.91 for the pre-test
and 0.92 for the post-test.
Qualitative Analysis of On-line scientific argumentation
The qualitative data collected from students’ on-line scientific argumentation was analyzed from two perspectives.
Each statement generated by an individual was classified into two different levels of claim, warrant, backing and
rebuttal, respectively. Data is considered to be non-argumentative statements. A level 1 claim is an argument
consisting of a claim without any data or fact. A level 2 claim is an argument consisting of a claim with data or fact.
A level 1 warrant is an argument consisting of a theory or principle without connection to the claim, or one which
does not clearly describe the theory. A level 2 warrant is an argument consisting of a claim with a clearly described
theory or principle. A level 1 backing is an argument only consisting of a backing without any connection to
claim/warrant, or one which does not clearly describe the connection among them. A level 2 backing is an argument
consisting of a claim with backing, and or with data or warrant. A level 1 rebuttal is an argument consisting of a
weak rebuttal without clear explanation. A level 2 rebuttal is an argument consisting of a claim with a clearly
identifiable rebuttal (Table 1). The cross-coder reliability is 0.91.
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In addition, students’ on-line scientific argumentation discourses were analyzed from a conceptual change
perspective. Each argumentation statement was determined to be correct, partially correct, or incorrect; and the
comparison between the correctness of pre-argumentation and post-argumentation is further performed by the t test.
The quality of conceptual change also was presented to see how students change their conceptions from pre- to postargumentation questions across seven topics. The cross coder reliability is 0.95.
Components
Claim
Warrant
Backing
Rebuttal
Table 1. Analytical Framework used for determining the quality of argumentation
Levels
Definition
Examples
An argument only consists with a The greater the concentration, the faster the
Level 1
claim without any data or fact.
reaction is.
An argument consists of a claim with I saw that the greater the concentration of HCl,
Level 2
data or fact.
the faster the reaction with marble is. Thus I
think that the greater the concentration, the
faster the reaction is.
An argument only consists with a The more molecules there are, the greater the
Level 1
theory
or
principle
without opportunity for collision.
connection to the claim, or not clearly
describes the theory.
An argument consists of a claim with The greater the concentration is, the faster the
Level 2
theory or principle.
reaction is. It is because the more molecules
there are, the greater the opportunity for
collision.
An argument only consists with a
I agree with David’s idea, because I had a
Level 1
backing without any connection to
similar experience that producing oxygen
claim/warrant, or not clearly describe experiment with high concentration of hydrogen
the connection among them.
peroxide.
An argument consists of a claim with I support Ann’s idea, because I have done the
Level 2
backing, and or with data or warrant.
concentration experiment (HCl react with
marble), which proves that the greater the
concentration, the faster the reaction is. So there
is greater intensity of the molecular collisions.
An argument only consists of a weak I do not agree with Thomas’s idea, because that
Level 1
rebuttal
and
without
clearly some person who drink high concentration wine
explanation.
would not get drunk at all.
An argument consists of a claim with I disagree with Jim’s idea that the lower the
Level 2
a clearly identifiable rebuttal.
concentration is, the faster the reaction is. The
lower the concentration, the smaller the amount
of molecules, thus the lower the opportunity for
collision.
Results
ANCOVA analysis of the Physical Science Conception test (PSCT)
The two-tier PSCT was developed to measure the degree of students’ conceptual change in physical science
conceptions. One-factor ANCOVA was conducted to examine the effects of instructional approaches using postPSCT scores as the dependent measures, and students’ pre-PSCT scores as the covariate. The results of the onefactor ANCOVA: specifically, instructional approaches (F=4.86, p= 0.029) reach a statistically significant effect on
the performance of post- PSCT. In summary, the OLSA group outperformed the traditional group on postperformance of Physical Science Conception test.
Multivariate analysis of the Physical Science Dependent Argumentation Test (PSDAT)
One-factor ANCOVA was conducted to examine the effects of instructional approaches using post-PSDAT scores as
the dependent measures, and students’ pre-PSDAT scores as the covariate. The results of the one-factor ANCOVA:
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specifically, instructional approaches (F=7.28, p= 0.008) reach a statistically significant effect on the performance of
post- and retention-PSDAT. In summary, the OLSA learning group outperformed the traditional group on postperformance of Physical Science Dependent Argumentation Test.
Multiple regression analysis
This section examines the relationship between students’ degree of conceptual change and their scientific
argumentation ability. Therefore, the stepwise regression method was used to explore whether the pre- PSDAT or
pre-PSCT test would be most important for predicting the post-PSDAT scores. Results indicated that the best single
predictor for post-PSDAT sores was the pre-PSCT, followed by pre-PSDAT scores. The standardized regression
coefficient for pre-PSCT, and pre-PSDAT were 0.41 and 0.31. Together pre-PSDAT and pre-PSCT accounted for
38.0% of the variance in post-PSDAT scores.
The Quantity and Quality of On-Line Scientific Argumentation
The experimental group’s student on-line scientific argumentation learning process was analyzed in two aspects:
nature and extent of argumentation ability and of conceptual change. The quality and quantity of students’
argumentation and conceptual change were presented in the following in order to manifest the nature and extent of
experimental group’s on-line scientific argumentation process.
Argumentation ability
All argumentation questions were designed to require 10-15 minutes for students to argue. With an average of six
students in a group, the mean frequency of arguments generated by each group in each question increased
progressively from 7.38 to 18.77 arguments during the 10-15 minutes from topic 1 to 7 (Figure 3).
20
18
16
14
12
10
8
6
4
2
0
Unit1
Unit2
Unit3
Unit4
Unit5
Unit6
Unit7
Figure 3. Distribution of mean frequency of arguments generated by each groups’ students across seven units
Repeated measures of ANOVA were used to examine any increases in mean frequency of arguments from topic 1 to
topic 7. The mean frequency of arguments generated by each student in each question significantly increased from
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1.17 to 3.04 from topic 1 to 7 (F=30.74, p<0.0001) (Table 2). Clearly, the group argumentation and individual
students’ argumentation pattern are similar. The post-hoc comparisons indicated that the number of arguments
generated by each student is statistically significantly greater when comparing later topics with earlier topics. This
clearly demonstrates that students’ ability to generate arguments indeed increased from topic 1 to topic 7 across the
semester.
Table 2. Repeated measures of ANOVA of arguments generated by each student across seven topics
F value of
repeated
measures
M
Topic 1
Topic 2
Topic 3
Topic 4
Topic 5
Topic 6
Topic 7
*
p<.05, **p<.01,
SD
1.17
2.20
2.68
2.05
1.91
2.38
3.04
***
p<.001; N=74.
.61
2.20
2.05
1.16
1.05
1.22
1.38
ANOVA
30.74***
(p=.000)
Post hoc comparisons
2>1***
3>1***，3>4**，3>5**
4>1***
5>1***
6>1***，6>4*，6>5***
7>1***，7>2**，7>4***，7>5***，7>6***
Each statement was categorized into two levels of claim, warrant, backing and rebuttal arguments. With an average
of six students in a group, the mean frequency of claim, warrant, backing and rebuttal arguments generated by each
group in each question from topic 1 to 7 ranged 2.29-13.3, 0.63-4.58, 0.75-4.27, and 0.18-1.77 (Figure 4).
14
12
10
8
6
4
2
0
1 2 3 4 5 6 7
Claim
1 2 3 4 5 6 7
1 2 3 4 5 6 7
Warrant
1 2 3 4 5 6 7
Backing
Rebuttal
Figure 4. Distribution of mean frequency of claim, warrant, backing and rebuttal arguments generated by each
groups’ students across seven units
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Table 3 shows that the mean frequency of claim, warrant, backing and rebuttal arguments generated by each student
for each question from topic 1 to 7 ranged from 0.37-2.16, 0.10-0.97, 0.12-0.69, and 0.03-0.29. The increase of
arguments was found to be statistically significant when comparing earlier topics with later topics through the use of
repeated measure of ANOVA in all aspects, regardless of claim, warrant, backing and rebuttal (F(claim)=32.69, p
<0.0001; F(warrant)=29.95, p <0.0001; F(backing)=11.63, p <0.0001; F(rebuttal)=6.06, p <0.0001). The post-hoc comparisons
indicated that the frequency of arguments is statistically significantly greater when comparing later topics with
earlier topics, regardless of claim, warrant, backing, and rebuttal in general.
Table 3. Multivariate Analysis of Covariance (MANCOVA) of Claim, Warrant, Backing, and Rebuttal Arguments
Generated by Each Student across seven topics
Level 1
Level 2
Total
Units
M
SD
M
SD M
SD
F*
Post hoc comparisons
CLAIM
32.69***
Topic 1
.31
.33 .05 .13
.37
.40
Topic 2
.47
.74 .08 .19
.55
.75
2>1*
Topic 3
3>1***，3>2***，3>4***，3>5***，3>6***，3>7***
1.81 1.40 .35 .81 2.16 1.62
Topic 4
.98
4>1***，4>2***，4>5**
1.07
.85 .33 .48 1.41
Topic 5
.58
5>1***，5>2***
.86
.53 .23 .31 1.09
Topic 6
.82
6>1***，6>2***，6>5**
1.14
.76 .26 .29 1.40
Topic 7
.76
7>1***，7>2***，7>5***
1.23
.75 .22 .24 1.44
WARRANT
29.95***
Topic 1
.31
1>3***，1>4***
.41
.30 .08 .14 .48
Topic 2
1.13
2>1***，2>3***，2>4***，2>5**，2>6*，2>7*
.68
1.04 .30 .36 .97
Topic 3
.07
.21 .03 .11 .10
.27
Topic 4
.09
.27 .08 .22 .17
.32
Topic 5
.46
5>3***，5>4***
.25
.33 .25 .33 .50
Topic 6
.43
6>1*，6>3***，6>4***，6>5*
.50
.40 .11 .18 .61
Topic 7
.42
7>1**，7>3***，7>4***，7>5*
.47
.35 .15 .20 .62
***
BACKING
11.63
Topic 1
1>5***，1>6**
.23
.33
.06 .11 .29
.34
Topic 2
2>1***，2>3***，2>4**，2>5***，2>6***
.49
.70
.14 .29 .64
.80
Topic 3
3>5**，3>6**
.11
.33
.16 .36 .27
.45
Topic 4
4>5**，4>6**
.11
.24
.18 .36 .28
.45
Topic 5
.02
.08
.10 .19 .12
.23
Topic 6
.05
.11
.09 .16 .14
.19
Topic 7
7>1***，7>3***，7>4***，7>5***，7>6***
.38
.39
.32 .41 .69
.70
***
REBUTTAL
6.06
Topic 1
.01
.06
.02 .06 .03
.08
Topic 2
.03
.15
.01 .06 .04
.18
Topic 3
.03
.13
.11 .44 .15
.52
Topic 4
.03
.11
.16 .32 .19
.36
4>1***，4>2***
Topic 5
.05
.11
.15 .26 .20
.32
5>1***，5>2**
Topic 6
.10
.22
.13 .22 .23
.39
6>1***，6>2***
Topic 7
.18
.29
.11 .19 .29
.42
7>1***，7>2***，7>3***，7>5*
*
**
***
Note: p<0.1, p<0.01, p<0.001; N=74.
Each statement generated by students was further categorized into two levels of claim, warrant, backing and rebuttal
arguments in order to reveal its quality. The mean frequency of two levels of arguments generated by each group in
each question shows a growing pattern overall, regardless of levels of claim, warrant, backing and rebuttal argument
(Table 3). Repeated measures of ANOVA showed that an increase of level 1 arguments was found to be statistically
significant when comparing earlier topics with later topics in all aspects, regardless of claim, warrant, backing and
rebuttal (F(claim)=53.50, p <0.0001; F(warrant)=23.88, p <0.0001; F(backing)=14.59, p <0.0001; F(rebuttal)=3.03, p <0.005).
The increase of level 2 arguments was also found to be statistically significant when comparing earlier topics with
206
later topics in all aspects, regardless of claim, warrant, backing and rebuttal (F(claim)=9.38, p <0.0001; F(warrant)=11.26,
p <0.0001; F(backing)=5.62, p <0.0001; F(rebuttal)=7.89, p <0.005).
Conceptual Change
The nature of each argument was judged and classified into three categories as correct, partially correct, and
incorrect. The results show that the mean score of correct conceptions for each argument generated by each student
increased from pre- to post- argumentation questions across all 7 topics, and 6 topics reached a statistically
significant difference level (Ttopic 1=2.25, p=0.027; Ttopic 3=3.31, p=0.001; Ttopic 4=4.16, p=0.000; Ttopic 5=7.18,
p=0.000; Ttopic 6=5.05, p=0.000; Ttopic 7=3.96, p=0.000). The mean score of partially correct conceptions decreased
from pre- to post-argumentation for three topics and only one of the topics reached a statistically significant
difference level (Ttopic 7=2.82, p=0.006), and slightly increased for three topics. The mean frequency of incorrect
conceptions decreased from pre- to post-argumentation for about six topics, and only one of the topics reached a
statistically significant difference level (Ttopic 5=5.15, p=0.000) (Table 4).
Table 4. Analysis of the correctness of conceptions for each argument generated at pre- and post-argumentation
question by each student across seven topics
Pre-argumentation
Post-argumentation
Mean
T
Sig
difference
M
SD
M
SD
Topic 1
C
.66
.66
.89
.72
.23
2.25*
.027
PC
.45
.50
.32
.40
-.13
-1.62
.110
IC
.07
.18
.05
.20
-.02
-.62
.535
Topic 2
C
.74
.74
.97
.99
.23
1.71
.091
PC
.64
.75
.81
.82
.18
1.42
.160
IC
.04
.20
.01
.12
-.03
-1.00
.321
Topic 3
C
1.50
1.49
2.72
3.07
1.22
3.31**
.001
PC
.36
.73
.45
1.17
.08
.47
.641
IC
.20
.55
.20
.60
.00
.00
1.000
Topic 4
C
1.32
1.27
2.00
1.39
.68
4.16***
.000
PC
.58
.91
.57
.76
-.01
-.12
.908
IC
.12
.44
.05
.23
-.07
-.140
.167
Topic 5
C
.79
.80
1.56
1.09
.77
7.18***
.000
PC
.47
.60
.33
.46
-.14
-1.70
.094
IC
.69
.81
.19
.40
-.50
-5.15***
.000
Topic 6
C
1.49
.93
2.28
1.52
.79
5.05***
.000
PC
.36
.47
.37
.48
.01
.21
.838
IC
.12
.23
.08
.22
-.04
-1.39
.169
Topic 7
C
1.59
.96
2.17
1.23
.57
3.96***
.000
PC
.88
.60
1.13
.85
-.77
2.82*
.006
IC
.23
.29
.16
.26
-.07
-1.61
.111
Note: C: correct conceptions; PC: partial correct conceptions; IC: incorrect conceptions; N=74.
Conclusions and Discussions
This study reports a Recurrent On-Line Synchronous Scientific Argumentation learning program that was developed
based on the conceptual change and scientific argumentation theories in order to promote 8th grade students’
conceptual change and scientific argumentation ability in a physical science context. This study is a major step from
207
previous Web-based instructional learning programs, as it brings well-developed conceptual change and scientific
argumentation pedagogy theories and models into Recurrent On-Line Synchronous Scientific Argumentation
learning. In addition, our learning environment contains two layers of template to provide students’ guidance and
support in constructing a good argument. It also provides the advantage of real time argumentation, so students can
receive prompt rebuttals to their arguments. This helps to make learning more effective.
The results of this study are quite positive as they demonstrate that On-Line Argumentation learning is far more
effective than conventional instruction for promoting students’ conceptual change and scientific argumentation. Our
results add positive documentation to the current research that students who receive a Web-based learning course can
perform better than a conventional group’s students in their physical science concept construction. In addition, we
argue that most computer-assisted learning studies cannot effectively change students’ alternative conceptions or
science learning because their instructional materials are not developed based on solid theories or models of
conceptual change or science learning(She & Lee, 2008; Liao & She, 2009; Yeh & She, 2010). This study supports
the idea that including argumentation and conceptual change theories into the design of Recurrent On-Line
Synchronous Scientific Argumentation learning are important for success.
In addition, the results of the on-line scientific argumentation process indicated that the amount of arguments
generated by student is significantly greater when comparing later topics with earlier topics, regardless of level 1 or
level 2. It clearly demonstrates that students’ ability to generate arguments indeed increased from topic 1 to topic 7
across the semester. Moreover, the mean frequency of arguments increased significantly from earlier topics to later
topics, regardless of claim, warrant, backing, and rebuttal. These results demonstrated that our design indeed
improves the quantity and quality of argumentation in the physical science context, regardless of the data collected
from tests or on-line scientific argumentation process.
Our results demonstrate that students’ argumentation significantly improves across a semester-long intervention of
argumentation in a physical science context. The breakthrough we made fully supports Osborne et al.’s suggestions
that a recurrent opportunity for students to be involved in argumentation may make difference (Osborne et al., 2004).
Our results also confirmed that constructing a good argument is not a simple task and that students need guidance
and support to help them scaffold and build their sense of an effective argument. With the supports of writing frames,
which indeed cultivate their ability to generate claim, warrant and backing arguments fairly quick except rebuttal.
This clearly supports the claim that the on-line synchronous argumentation learning environment, with the support of
writing frames, indeed speeds up students’ ability to generate better and higher level arguments within very short
period and continuously grow till the end.
Moreover, our data found that students’ ability to generate argumentation is not quite stable across a semester. It is
rather difficult to generate rebuttal arguments and takes a much longer period to cultivate compared to the claim and
warrant arguments. Our data indicated that the quality and quantity of claim and warrant arguments become stable
after topic 5, and rebuttal arguments increased gradually all the way from topic 1 through topic 7. It indicated the
need to provide students with recurrent opportunities to use argumentation in science in order to stabilize their ability
of using argumentation and increase their level of argumentation.
The mean frequency of correct conceptions for arguments generated by each student increased from pre- to postargumentation questions across all 7 topics, and 6 topics reached a statistically significant difference level. The
finding is quite positive and promising with regards to changing students’ alternative conceptions from both the
assessment and on-line argumentation process. It is clear that the success in conceptual change is due to the design of
Recurrent On-Line Synchronous Scientific Argumentation learning, which organizes conceptual change into a series
of pre-, experiment-related, and post-argumentation activities. Our results demonstrate that our design of taking
conceptual change ideas is critical for successfully changing students’ conceptions through a series of argumentation
activities, specifically the ideas of creating dissonance, which provide an opportunity for them to experience the
dissonance and become further dissatisfied with their prior conceptions (She, 2004; Hewson & Hewson, 1988;);
providing plausible mental structures for students to reconstruct more scientific conceptions (She, 2004); and
actively engaging students in the group discussions to shape their knowledge construction process and changing
conceptions (Driver, 1995; Venville & Treagust, 1998).
Finally, the regression results show that the best single predictor for post-PSDAT sores was the pre-PSCT, followed
by pre-PSDAT scores. It demonstrated that constructing arguments of quality will be restricted and hampered
208
without the sources of specific knowledge or relevant scientific evidence. It implies that students who hold less
alternative conceptions are more likely to perform better in the post-Physical Science Dependent Argumentation
Test.
Acknowledgements
This research is based in work supported and funded by the National Science Council (NSC 95-2522-S-009-001MY3), Taiwan, R.O.C.
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