Arguing to learn and learning to argue

48 Pages·2009·0.32 MB·English

Arguing to learn and learning to argue
Larson, J. R., Christensen, C., Abbott, A. S., & Franz, T. M. (1996). Diagnosing groups: Charting the flow of
information in medical decision-making teams. Journal of Personality and Social Psychology, 71(2), 315-330.
http://www3.interscience.wiley.com/journal/116838563/abstract

Stanford University makes this peer-reviewed final draft available under a Creative Commons Attribution-
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author.

Arguing to learn and learning to argue: Case studies of how students'
argumentation relates to their scientific knowledge

Claudia von Aufschnaiter1, Sibel Erduran2, Jonathan Osborne3, & Shirley
Simon4

1University of Hannover 2Graduate School of Education
Department of Physics University of Bristol
Physics Education 35 Berkeley Square
Bismarckstrasse 2 Bristol BS8 1JA
30173 Hannover United Kingdom
Germany
Email: [email protected]

3King‟s College London 4Institute of Education,
Department of Education and Professional Studies University of London
Franklin-Wilkins-Building 20 Bedford Way
150 Stamford Street London WC1H 0AL
London SE1 9NN United Kingdom
United Kingdom

Revised manuscript submitted to Journal of Research in Science Teaching, January 2007
Arguing to learn and learning to argue 1

Abstract
In this study Junior High School students‟ processes of argumentation and cognitive
development occurring in science and socio-scientific lessons were investigated. Detailed
studies of the relationship between argumentation and the development of scientific
knowledge are few. Using video and audio documents of small group and classroom
discussions, the quality and frequency of students‟ argumentation was analyzed using a
schema based on the work of Toulmin (1958). In parallel, students‟ development and usage of
scientific knowledge was also investigated drawing on a schema for determining the content
and level of abstraction of students‟ meaning making. These two complementary analyses
enabled an exploration of their impact on each other. The microanalysis of student discourse
showed that (a) when engaging in argumentation students draw on their prior experiences and
knowledge; (b) such activity enabled students to consolidate their existing knowledge and
elaborate their science understanding at relatively high levels of abstraction. The results also
suggest that students can show a higher quality of argumentation that consists of well
grounded knowledge of a relatively low level of abstraction. The findings suggest that the
main indicator of whether or not a high quality of argument is likely to be attained is students‟
familiarity and understanding of the content of the task. The major implication of this work
for developing argumentation in the classroom is the need to consider the nature and extent of
students‟ content specific experiences and knowledge prior to asking them to engage in
argumentation.
Introduction
Within the last years, an increasing number of research projects have focussed on
argumentation in school science teaching (e.g., Boulter & Gilbert, 1995; Driver, Newton, &
Osborne, 2000; Duschl & Osborne, 2002; Kelly & Duschl, 2002; Martins, Mortimer,
Osborne, Tsatsarelis, & Jiménez-Aleixandre, 2001; Zohar & Nemet, 2002). The theoretical
Arguing to learn and learning to argue 2

underpinnings of these projects refer to three different arguments for enhancing
argumentation skills which briefly summarized are:
(1) Scientists engage in argumentation to develop and improve scientific knowledge: “A
central activity for scientists is to construct and use arguments about which of the
imaginative conjectures for a puzzling phenomenon are the most convincing in light of
that evidence and, of course, to obtain additional evidence when the available evidence
is insufficient or lacking” (Lawson, 2003, p. 1387).
(2) The public has to use argumentation to engage in scientific debates: “Our decision-
making is often based on information available through press and media accounts,
which may report contested claims arising from different sources of evidence.
Evaluating such reports is not straightforward, as it requires the ability to assess the
validity and reliability of evidence used in scientific arguments” (Simon, Osborne, &
Erduran, 2003, p. 200).
(3) Students‟ learning of science requires argumentation: “Talking offers an opportunity for
conjecture, argument and challenge. In talking, learners will articulate reasons for
supporting particular conceptual understandings and attempt to justify their views.
Others will challenge, express doubts and present alternatives, so that a clearer
conceptual understanding will emerge” (Newton, Driver, & Osborne, 1999).
In all of these three arguments, the coordination of argumentation and scientific
knowledge plays an important role. However, the third point stresses the role of
argumentation as a heuristic to develop an understanding of scientific concepts. Students not
only have to learn to develop valid arguments but will also learn science while arguing (e.g.,
Erduran, Simon, & Osborne, 2004; Millar & Osborne, 1998; Jiménez-Aleixandre & Pereiro-
Munhoz, 2002; Osborne, Erduran, Simon, & Monk, 2001; Schwarz et al., 2003). The case for
the inclusion of argumentation as a form of pedagogy comes from the increasing empirical
evidence emerging from the work of social psychologists that the knowledge and
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understanding of school-age children can be facilitated by collaborative work and contrasting
views between peers (Damon & Phelps, 1989; Doise & Mugny, 1984; Howe, Tolmie, &
Mackenzie, 1995; Howe, McWilliams, & Cross, 2005); and from empirical studies conducted
in the classroom (Zohar & Nemet, 2002, Mercer et al, 2004).
But how is ability to engage in argumentation dependent on scientific understanding?
Currently, there is an ongoing debate whether poor performance in argumentation is a result
of a lack of general competencies or whether it is caused by insufficient content specific
knowledge (e.g., Hogan & Maglienti, 2001; Lawson, 2003; Kuhn, 1991; Koslowski, 1996;
Sadler, 2004). This debate suggests that scientific rationality requires a knowledge of
scientific theories, a familiarity with their supporting evidence, and the opportunity to
construct and/or to evaluate their interrelationship (Osborne, Erduran, & Simon, 2004).
However, the detailed nature of the interrelationship between argumentation and science
learning has not been explored in naturalistic contexts of the science classroom.
The objectives of this research, therefore, were to explore:
a) How students incorporate their content specific knowledge in classroom lessons based
on argumentation.
b) How students develop and improve their understanding of science in these lessons.
c) How the quantity and quality of students‟ arguments are influenced by students‟ content
specific knowledge.
These questions were explored through a set of case studies of video-documented lessons
on science and socio-scientific issues for which students were asked to engage in
argumentation. By means of an analysis of the transcripts both the quantity and quality of
students‟ arguments and students‟ cognitive development were considered and their
interrelationship examined.
Arguing to learn and learning to argue 4

Background and Theoretical Framework
Argument in Science Teaching
Research with a focus on classroom discourse during the teaching and learning of science
emerged in the 90s (e.g., Driver, Newton, & Osborne 2000; Lemke, 1990; Martins et al. 2001;
Newton, Driver, & Osborne 1999). Within this area, research on argumentation has emerged
as a means of facilitating student-student and student-teacher discourse and led to the
development of theoretically based frameworks for its analysis – predominantly based in the
work of Toulmin (1958) (e.g., Jiménez-Aleixandre, Bugallo, & Duschl, 2000; Kelly, Drucker,
& Chen, 1998; Osborne, Erduran, Simon, & Monk, 2001; Schwarz et al., 2003; Zohar &
Nemet, 2002). From Toulmin‟s perspective, the elements of an argument are claims, data,
warrants, backings, qualifiers, and rebuttals. The claim is the conclusion whose merits are to

be established; the data are the facts which are appealed to support the claim; the warrants are
the reasons that establish the connections between the data and the claim; whilst the backing
is the theoretical assumptions on which the warrants rest. Qualifiers simply establish the
boundaries of the claim and rebuttals are arguments which attempt to refute the elements of
an argument.
For most of these projects, researchers have focussed on the processes of argumentation in
scientific communities, either in classrooms or amongst scientists themselves. Using video, or
audio, and by transcribing the discourse, teachers‟ and students‟ arguments have been
investigated both in terms of their quality and quantity. Results would indicate that teaching
of argument can increase the quality of students‟ arguments and the frequency with which
students use arguments (e.g., Kelly, Drucker, & Chen, 1998; Osborne, Erduran, & Simon,
2004; Zohar & Nemet, 2002).
In addition, some investigations have also focussed on students‟ understanding of science
itself. Basically, these studies use either a descriptive analysis of the content that students
deploy during argumentation or a pre-post-test design in order to examine the increase in
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students‟ knowledge (e.g., Jiménez-Aleixandre, Bugallo, & Duschl 2000; Jiménez-Aleixandre
& Pereiro-Munhoz, 2002; Leach, 1999; Mason, 1996; Zohar & Nemet, 2002). Results based
on either approach indicate that an increase of students‟ conceptual understanding occurs
when they are exposed to argumentation. Nevertheless, as valuable as this work is, a pre-post
analysis of students‟ knowledge does not answer in detail how students incorporate and
develop conceptual understanding while arguing.
Development of Scientific Knowledge
For the last three decades a large body of research has concentrated on students‟ development
of scientific knowledge (e.g., Duit, 1999; Duit & Treagust, 1998; Hewson, 1996; Limón &
Mason, 2002; MacBeth, 2000; Schnotz, Vosniadou, & Carretero, 1999). Basically, these
studies draw on a constructivist epistemology and have aimed to determine students‟
conceptual change as well as to identify teaching strategies that promote such a change (e.g.,
Duschl & Gitomer, 1991; Hewson, 1996). However, although the theoretical frameworks of
these projects often address students‟ learning processes, the majority of the empirical
procedures investigate the products of students‟ learning rather than the processes of student
learning. Typically, such research uses pre-post-test to investigate students‟ concepts prior to
and after instruction but the nature of the process of conceptual change is mainly not explored
(e.g., Hestenes, Wells, & Swackhamer, 1992; Hake, 1998; Dykstra, Boyle, & Monarch,
1992). Thus, from the current status of research, it can be concluded that major issues of the
processes by which conceptual development takes place are still theoretically and empirically
vague (e.g., diSessa, 2002). Generally, we cannot yet explain in detail why teaching strategies
that attempt to promote conceptual change are often unsuccessful. To achieve this objective, it
is necessary to know how students make sense of learning material offered to them and how
this material contributes and fosters students‟ conceptual development. In short, it would be
necessary to trace how students create meaning out of what the learning experiences they are
offered and how they deploy their own knowledge and understanding in tasks and problems.
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To obtain such insight into students‟ development of scientific understanding one of the
authors has developed a theoretical framework and methodology that allows a detailed
description of students‟ conceptual development (e.g., C. v. Aufschnaiter & S. v.
Aufschnaiter, 2003; C. v. Aufschnaiter, 2006). A variety of video-studies, mainly in the area
of electrostatics and electrodynamics have been used to identify and theoretically describe the
processes of knowledge development in students. These studies, focused on students aged
between 14 and about 25, thus, at high school and university level and, rather than
documenting content specific descriptions of the knowledge students did “show” and also
what was absent from their understanding, the work tried to identify and theorize the patterns
by which these processes occur instead. From this work, it became apparent that at least three
dimensions could be used to describe and theorize students‟ development of knowledge:
content, level of abstraction1, and time. With these dimensions, it was shown that that, no
matter what the age and the extent of their experiences, students‟ learning can be
characterised as an increasing ability to: (a) integrate content elements and to sustain an
appropriate thematic focus; (b) to consider general rules and laws rather than focusing on
single objects and phenomena; and (c) to solve tasks and problems more quickly.
Hence, in the research reported here, this framework has been used to analyse the
dimensions of content and level of abstraction in students‟ argumentative discourse, each of
which is further described below. The third dimension of time was not explored as such an
analysis would have required a mode of transcription that included time marks every few
seconds – a feature which was not included when the original transcripts were produced.
Nevertheless, even without this information, the framework does permit the analysis to trace
students‟ development of knowledge over time in much more detail than that afforded by
other studies on conceptual change.
Content. Although the description of scientific appropriateness of students‟ (situated)
understanding has predominated in research in science education (e.g., Duit, 2006), we would
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argue that it is the ability of the student to integrate separate aspects of such knowledge which
is also an important factor in cognitive development. For instance, there is a significant
difference between whether a (very young) student is able to repeat the word “force” or
whether the student can use this expression appropriately in a context (e.g., “I needed lots of
force when I hit the ball”). If the student is also able to discern that the movement of a
particular object (e.g., a red ball) is a result of an acting force or, even more, that different
forces can be attributed to this particular situation, his/her knowledge has become more
expansive. In addition to integrating aspects of their knowledge students should also be able
to differentiate which aspects are important within a specific situation and which are not. For
instance, in terms of force it is not important whether the moving ball is red or green. To
distinguish variables which are significant to the concept of force (e.g., the velocity of the
ball) from those which are not (e.g., the colour of the ball) Marton and Booth (1997) suggest
that students need to explore content specific variation systematically. Similarly we would
argue that students need to be able to discern those aspects which are important in order to
describe and (later on) conceptualise specific phenomena. Even if all the relevant elements of
content are neither recognised nor integrated in a complete (correct) physics description, those
that are enable students to move towards improving their understanding of the phenomenon in
focus.
Abstraction. Studies by Piaget and Neo-Piagetian theorists have provided a useful means
of describing (general) cognitive development (e.g., Piaget & Garcia, 1991; Case, 1997) and
investigating the content specific development of students‟ understanding and are, therefore, a
body of work on which we draw. The theoretical framework outlined above distinguishes
between an understanding that focuses on single objects and phenomena (“concrete”) and an
understanding that focuses on the principles that govern a domain, that is, a set of classes of
objects and phenomena that are considered “abstract”. Even though this model is similar to
Piagetian notions of cognitive development it differs from such general descriptions in that it
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regards content knowledge as a specific feature of higher level reasoning. This model
distinguishes four areas of abstraction which each contain two to three levels (Table 1):
Area I Within the concrete area (levels of Objects, Aspects, and Operations), students
grapple and (mentally) deal with concrete situations and objects, that is, they
consider single phenomena, describe observations and experiences, link physics
expressions to particular objects/phenomena but not to physics concepts or
theories.
Area II Within the abstract-static area (levels of Properties and Events), students develop a
more general understanding within which they summarize classes of phenomena
and objects (establish a conceptual understanding). Furthermore, students combine
different general properties into a rule-based understanding. However, the
relationship between the properties is seen as static, that is, students cannot
mentally create functional variation besides connecting values (e.g., small x/small
y versus big x/big y).
Area III Within the abstract-dynamic area (levels of Programmes and Principles) students
establish a functional relationship in which at least one variable is considered to
vary dynamically. Typically, physics laws are of this form (e.g., the more x/the
more y).
Area IV Within the systemic area (levels of Connections, Networks, and Systems) a more
expanded understanding of dynamic relationships between different connections of
more than two variables is developed. This area is rarely seen amongst learners.

[Insert Table 1 about here]

Empirical results with high school students show that most of students‟ (mental) activities
can be ascribed to the concrete and abstract-static areas. Indeed, in the work undertaken so far
Arguing to learn and learning to argue 9

the use of area IV has not been found by any student (e.g., C. v. Aufschnaiter & S. v.
Aufschnaiter, 2003).
Taken together, these two dimensions of content and abstraction are a useful tool to
investigate students‟ knowledge as well as to describe what a learning environment (either
tasks or instruction) requires from students. Both dimensions can be used in order to relate
students‟ understanding to the demands made by the instruction. Furthermore, used to analyse
how students‟ knowledge is developing at different points in their instruction, the dimensions
can provide a detailed description of the dynamic nature and manner in which students‟
learning has occurred. For instance, when students grapple a second or a third time with
specific aspects of the concept force, it can reveal how they can integrate more content
elements or that they may reach a higher level of abstraction.
Data
Overview of the Study and Participants
Research was conducted in essentially two phases. The first phase took place from September
1999 till September 2000. Here, material for use in argument-based lessons was developed
and 12 teachers were trained on skills of promoting argumentation in science lessons (e.g.,
Osborne, Erduran, & Simon, 2003; 2004). This research draws on work conducted in the
second year of this work with a subset of six teachers who had made progress in their ability
to promote argumentation were chosen to repeat their teaching on argument. The teachers
involved also incorporated a series of nine argument-based lessons in grade 8 classes of
London Junior High Schools across the course of a year. Whereas the first and the final lesson
were based on a socio-scientific issue (for an example see Table 2) the lessons in-between had
a science focus. Both socio-scientific lessons were video and audio-recorded in order to
evaluate the characteristics of the teachers‟ approach to argumentation as well as their
progress. Furthermore, in each class two groups of students were taped and transcribed in
order to develop a schema for evaluating the quality of their argumentation. Typically, each