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PRINCIPLE 10:
Designers Should Help Learners Understand and Internalize
the Structure of Argumentation
Ingo Kollar, Frank
Fischer, & James D. Slotta
The original paper,
entitled
“Internal and External
Collaboration Scripts in Web-based Science Learning at Schools,”
was presented at the 2005 Computer-Supported Collaborative
Learning Conference in Taipei, Taiwan.
This study by Drs. Kollar,
Fischer, and Slotta addresses a key challenge in developing
worthwhile science, technology, engineering, and mathematics
(STEM) learning environments. Current views of teaching and
learning support authentic and inquiry-oriented instructional
approaches. These let students explore scientific phenomena and
problems in much the same way that STEM professionals do.
Particularly with new networked computer technologies, students
are increasingly able to collaboratively generate and
investigate researchable questions, form hypotheses, conduct
experiments, and interpret data (van Joolingen, de Jong,
Lazonder, Savelsbergh, & Manlove, 2005). While learning
scientists and educational researchers have made great progress
in this regard, many students don’t know how to work and learn
collaboratively. They need to learn how to do this in the
context of authentic scientific inquiry (Quintana et al., 2004).
This study looks at a
promising and well-researched web-based inquiry learning
environment that supports collaborative inquiry and learning. In
particular, the study investigated how collaboration scripts
(O’Donnell, 1999) can improve how people argue collaboratively
and gain knowledge.
All learners
have internal scripts. These refer to the learners’ individual
procedural knowledge that guides them in how they argue (Schank
& Abelson, 1977), and they play a key role in successful
collaborative argumentation.
Collaboration scripts can help
improve collaborative argumentation by prescribing certain
activities, sequences, and roles (Kollar, Fischer, & Hesse, in
press). For example, scripts can specify that one learner should
advocate a specific hypothesis while another learner should
attack this hypothesis. The idea is that when students engage in
these activities, sequences, and roles, they elaborate content
more deeply and acquire more individual knowledge than they
would without a collaboration script.
Of course, learners possess widely varying
ideas about collaboration and different capabilities for
argumentation. These differences might require different
collaboration scripts for learners to achieve the benefits of
argumentation.
Why Support Collaborative
Argumentation?
STEM instructional designers
should consider focusing on collaborative argumentation. That’s
because the
ability to engage in argumentation is an important lifelong
learning skill that schools should teach (Linn, Davis, & Eylon,
2004). In addition,
debating with peers about hypotheses, data, or evidence helps
learners deeply elaborate science content (Sandoval, 2003). This
supports the learning of specific scientific knowledge in robust
and useful ways. Traditional approaches that teach content
separate from argumentation leave students with a shallow
understanding of the concepts and lacking in applying meaningful
argumentation skills, such as using evidence to support claims.
What Is the Structure of Collaborative
Argumentation?
This study builds on prior
research that examined the kinds of collaborative argumentation
that support learning (Andriessen, Baker, & Suthers, 2003).
Arguments have two kinds of structure. One is the
structure of single arguments; the other involves argumentation
sequences. Single arguments include
(1) data
that provides evidence on which the argument relies, (2) a
claim
that states a position, and
(3) a reason stating why the data supports the claim (Toulmin,
1958).
Argumentation sequences involve (1) arguments, (2)
counterarguments, and (3) integrative arguments (Leitao,
2000).
How Can Collaborative Argumentation Be
Supported?
Previous studies by these
researchers showed that collaboration scripts in
computer-supported learning environments improved collaborative
argumentation and enhanced learning (Weinberger, Stegmann, &
Fischer, 2005). However, one key question about external scripts
that has yet to be answered is how structured they should be.
Some researchers have experimented with more unstructured
scripts that provide loose constraints for activities,
sequences, and roles (e.g., Baker & Lund, 1997). Others have
used highly structured scripts that provide very detailed
instructions concerning activities, sequences, and roles (e.g.,
Weinberger et al., 2005).
This study considered the
internal scripts that learners already have when they enter an
inquiry learning session. That’s important because preexisting
internal scripts might conflict with the external script, while
other internal scripts might help students master and learn the
external scripts. The researchers assumed that internal scripts
also vary in terms of structure.
Some individuals
might know that they should make their reasons explicit in
arguments and that good argumentation sequences feature
counterarguments and integrative arguments. Others might not
have that knowledge and rather develop arguments that simply
rely on claims and skip the development of counterarguments or
integrative arguments. The study examined whether learners with
differently structured internal scripts benefit from differently
structured external scripts and how the interplay between
internal and external scripts affects learning collaborative
argumentation and more specific scientific knowledge. The study
did so using the Web-Based Inquiry Science Environment
(WISE), which was developed by researchers at the University of
California at Berkeley and has been researched extensively.
How Can Learning Technology Help
Learners Understand the Structure of Argumentation?
In order to study differently structured
internal and external scripts in WISE, the researchers looked at
both process measures and outcome measures.
Process measures examined effects of internal and external
scripts on the quality of collaborative argumentation. Outcome
measures examined individual learning. Measures assessed more
general knowledge of argumentation as well as more specific
knowledge associated with the scientific domain.
The researchers started by
examining the internal scripts of 98 high school students, two
weeks before the actual collaborative inquiry session took
place. The students took an assessment that had them identify
“good” and “bad” examples in samples of scientific
argumentation. The students who were better at this task were
judged to have more structured internal scripts. The scores were
used to split the students into two groups. The half of the
students with higher scores were classified as having
high-structure internal scripts; the others were classified as
having low-structure internal scripts. Collaborative pairs were
then assembled consisting of either two high-structure
individuals or two low-structure individuals. This resulted in a
“2 x 2” experimental design that had four combinations of
internal/external scripts (high/high, high/low, low/high,
low/low).
The pairs of students then
completed one of two versions of a
WISE
investigation, “The Deformed Frogs Mystery” (Linn, Shear, Bell,
& Slotta, 2004). The investigation asked learners to contrast
two competing hypotheses (parasitic vs. environmental) for
widespread physical deformities in frogs. The hypotheses were to
be discussed across five content-specific units. Each unit
offered students a range of various scientific data sources
(e.g., photographs, maps, reports), which could be used to
explore the two hypotheses. At the end of each unit, learners
were asked to discuss their hypotheses in light of the
information. Students were then instructed to record their
arguments supporting the two hypotheses in a text-entry box.
In the
low-structure version of the WISE investigation, students were
simply instructed to record their arguments into a plain text
box. In the high-structure version (see Figure 1) instructional
text and prestructured text boxes prompted learners to construct
arguments using data, claim, and reason, and construct
argument sequences consisting of arguments, counterarguments,
and integrative arguments. Each box specified which of
the two learners had to create an argument component and
provided sentence starters for each component (e.g., “It was
found that…” for data). Each student was instructed to advocate
for just one of the two hypotheses, with the assignment
switching several times during the course of the project. To
ensure that students internalized the argument structure, the
degree of structure was faded across the units, so that the
final unit in the high-structure environment was similar to the
final unit in the low-structured environment.
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Figure
1:
Screenshots of the high-structured external collaboration script
(left screen: introductory text; right screen: prestructured
text boxes to be filled in by the participants). |
Each pair of
students worked together on the investigation for two hours,
relying entirely on the instructions and guidance provided in
the WISE investigation. After completing the investigation, each
student completed two outcome measures. One assessed students’
knowledge of argumentation. It asked learners to list the
components of good arguments and argument sequences and to give
examples of complete arguments and argument sequences. The other
measure assessed each student’s knowledge of the embedded
scientific concepts. Five open-ended questions asked students to
describe the mechanisms that might cause the frog deformities
and how one could formally test them.
What Happened When This Technology Was
Actually Used?
As expected,
scores on the test of knowledge about argumentation showed that
the high-structure external script resulted in greater learning
about argumentation. Specifically, the students who completed
the high-structure version of the WISE investigation showed
greater knowledge of argumentation than the students who
completed the low-structure version and were better able to
construct appropriate arguments and argument sequences. The
difference was statistically significant, meaning that there was
less than a 1 in 20 chance that the difference between the two
groups might have occurred by chance. The effect was the same
for students with low-structure internal scripts as for students
with high-structure internal scripts. Technically, this means
that there was no statistically significant “interaction”
between internal and external scripts.
Scores on the
scientific knowledge test showed that students with
high-structure internal scripts learned more of the embedded
scientific content than students with low-structure internal
scripts. The group with the lowest score on the knowledge test
was the group whose internal and external scripts were both low
structured. But overall there was no statistically significant
evidence that the high-structure external script improved
student learning of the embedded scientific content. The
researchers also conducted detailed analyses of argumentation by
coding transcripts of the recorded discussions of some of the
students. Examples and analyses are presented in the original
paper but are not included in this summary.
What Should Designers Do to Help
Learners in Collaborative Argumentation?
This study showed that within
a relatively short intervention (two hours) it is possible for
students to learn useful information about the structure of
scientific argumentation. This included the appropriate
structure of scientific arguments as well as the appropriate
structure of argument sequences. This study also showed that
students who had relatively more knowledge about argument
structure learned more of the domain-specific scientific
knowledge when participating in collaborative inquiry-oriented
investigations than students with relative less knowledge about
argument structure. While the study did not show that providing
students with the high-structure external script helped them
learn more specific scientific knowledge, this is not entirely
surprising given the length of the intervention and the fact
that the students were also learning about argumentation
structure and sequences represented by those scripts. The
important point for STEM instructional designers is that
argument structure can be directly taught within a content-rich,
web-based inquiry environment and that learners who bring such
knowledge to inquiry-oriented environments learn more than
students who do not.
The study also provided a
useful illustration of a general way that STEM instructional
designers can support participation in scientific argumentation.
In a wide range of environments (both with and without
sophisticated technology), instructional designers can help
students construct scientific arguments using data, claims, and
reasons, and construct sequences consisting of arguments,
counterarguments, and integrative arguments. This study provided
valid examples of how more sophisticated designers might measure
learning of scientific argumentation as well as learning of
domain-specific scientific knowledge by participating in that
argumentation.
[1] This paper
was a winner of the 2005 Virtual Design Center's paper
competition, selected through an extensive review
process by the Virtual Design Center advisory board. The
above summary was prepared by the authors with the
assistance of the advisory board chair (Daniel T.
Hickey) and the project manager (Beaumie Kim). For more
information on how you could use this design principle
for your practice, you may contact the Virtual Design
Center (vdc@cet.edu) or the board representatives
(Daniel T. Hickey, dthickey@indiana.edu; Beaumie Kim,
bkim@cet.edu) and the authors (Ingo Kollar, i.kollar@iwm-kmrc.de;
Frank Fischer, f.fischer@iwm-kmrc.de; James D. Slotta,
slotta@tels.berkeley.edu).
[2] The development project was funded primarily by the
National Science Foundation and directed by Marcia Linn
and third author, James Slotta. For more information
visit www.wise.berkeley.edu
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