Educational technologies for teaching argumentation skills

359 Pages·2012·6.04 MB·English

by  Niels Pinkwart

Educational Technologies for Teaching
Argumentation Skills
Edited By
Niels Pinkwart
Clausthal University of Technology
Germany
&
Bruce M. McLaren
Saarland University
Germany
&
Carnegie Mellon University
USA
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CONTENTS
Foreword i
Preface iii
List of Contributors viii
CHAPTERS
1. Criteria for Designing and Evaluating Argument Diagramming
Tools from the Point of View of Argumentation Theory 3
Silvia De Ascaniis
2. A Framework for Analyzing Development of Argumentation
through Classroom Discussions 28
Marietta Sionti, Hua Ai, Carolyn Penstein Rosé and Lauren Resnick
3. Review of Evaluations of Argument Diagramming Tools in
Collaborative Learning 56
J. Dowell
4. Automated Analysis and Feedback Techniques to Support and
Teach Argumentation: A Survey 71
Oliver Scheuer, Bruce M. McLaren, Frank Loll and Niels Pinkwart
5. CoFFEE: An Expandable and Rich Platform for Computer-
Mediated, Face-to-Face Argumentation in Classroom 125
Rosario De Chiara, Ilaria Manno and Vittorio Scarano
6. How Tough should it be? Simplifying the Development of
Argumentation Systems Using a Configurable Platform 169
Frank Loll, Niels Pinkwart, Oliver Scheuer and Bruce M. McLaren
7. iARGUE: A Web-Based Argumentation Environment Integrating
Collaboration Scripting Support and Flexible Fading Techniques 198
Yannis N. Bouyias and Stavros N. Demetriadis
8. Policy World: A Cognitive Game for Teaching Deliberation 225
Matthew W. Easterday
9. Digital Dialogue Games and InterLoc: A Deep Learning Design
for Collaborative Argumentation on the Web 277
Andrew Ravenscroft, Simon McAlister and Musbah Sagar
10. Teachers' Use of the Argunaut System in the Classroom 316
R. De-Groot
Index 346
i
FOREWORD
Historically, argumentation, reasoning, and instruction have been inextricably
linked. In a wide range of pedagogical contexts, instructors traditionally engage
students in argumentation to make them better reasoners. “[A] good reasoner
should be able to generate arguments, providing supportive reasons to the claims
that are made…, consider arguments counter to his or her argument and be able to
refute them or to re-evaluate one’s own position in reference to them….”1
Given the vitality of this linkage, it is regrettable that across wide swaths of the
educational scene, the use of argumentation as a gauge of students’ understanding
is on the decline. Class sizes are too large for instructors to provide detailed
feedback on students’ written arguments, more objective measures of learning,
such as multiple-choice tests, are becoming the norm across the curriculum, and
distance learning environments are not necessarily conducive to robust argument.
Meanwhile, argumentation has become a “hot topic” of Artificial Intelligence
research. In the last few years, AI Journal special issues have devoted hundreds of
pages to computational models of argument, and new conference series devoted to
that topic have arisen and prospered. Argumentation research has implications for
the semantic web, multi-agent systems, social networks, decision support in
application areas, and educational technology.
A growing number of researchers have focused on using computer technology to
teach humans argumentation skills, either in general or in application areas. This
research has yielded intellectual products such as computational models of argument
schema with critical questions geared to specific course content, techniques for
integrating argumentation into human computer interfaces via argument diagrams,
and tools for engaging students in collaborative argument-making.
This focus on educational technologies for teaching argumentation skills, comes
just in time to assist two communities. First, these technologies may retard or
even reverse the decline in reliance on argumentation as a pedagogical medium

1James Voss and Mary Means (1991) “Learning to Reason via Instruction in Argumentation”,
Learning and Instruction 1, 337-350.
ii
and means for gauging student understanding. To the extent that instructional
argumentation systems reify pedagogically important elements of argumentation,
enable students to practice argumentation skills outside of class, and provide tools
for intelligently integrating source materials into arguments, they preserve and
extend the efficacy of argumentation as an educational tool. Second, these
educational technologies provide a practical context for evaluating AI’s new
computational models of argument; if the models are robust, they should be the
basis for instructional environments that help students learn, presumably an
objectively measurable effect.
Or is it? Ironically, in evaluating student learning with argumentation systems, we
often face a similar conundrum. Instructors can understand textual arguments, but
they do not have time to grade them. Computers work fast but they do not
understand textual argumentation. In order objectively to evaluate how well the
educational technologies work in teaching argumentation skills, it is tempting to
use those same objective measures, for instance, multiple-choice tests, that are
supplanting the more subjective, but arguably more probing “measures” based on
how well students argue.
As work progresses on new educational technologies for teaching argumentation
skills, therefore, researchers need to focus on developing new techniques for assessing
how well students learn argumentation skills. Fortunately, some are; researchers are
inventing ingenious assessment techniques harnessing computer-supported peer
review, the “diagnosing” of argument diagrams, and technological ways to enhance
the ability of objective tests to probe the depth of students’ understanding.
Kevin D. Ashley
Professor of Law and Intelligent Systems
Senior Scientist, Learning Research and Development Center
University of Pittsburgh
Pittsburgh, Pennsylvania
USA
iii
PREFACE
We have come a long way in pedagogy and educational technology to now be
positioned to support students in learning argumentation skills with software.
Unlike systems that focus on helping students gain well-defined knowledge and
problem solving skills, such as intelligent tutoring systems for mathematics,
computer support for argumentation, an ill-defined domain, is not a question of
evaluating arguments using strict rules and unbending laws and providing
definitive feedback on how to construct and improve arguments. It is typically
difficult to separate a good argument from a weak one – a single unsubstantiated
fact, one that may only be unsubstantiated in a subtle way, in a long line of
argumentation may ruin an otherwise sound and well-reasoned argument. Many
situations entail strong, and potentially winning, arguments both for and against a
position. Furthermore, the “facts” in many argumentation scenarios are not
necessarily immutable; they are often interpreted differently in different contexts
or by different individuals. In the law, for instance, initial decisions are often
overturned in appeals courts, as a new judge interprets a legal argument
differently than a prior judge. In short, developing software that can effectively
help students learn to discuss and argue in a well-reasoned way, while at the same
time inculcating the nuances of argumentation, is truly a daunting task, not the
least because argumentation itself is an ill-defined area of reasoning.
Nevertheless, the authors of the chapters in this e-Book, as well as a growing
number of researchers around the world, are aggressively tackling the task of
helping students learn argumentation with computer support. This e-Book is
aimed at summarizing their efforts and providing glimpses to the future of the
field.
But why, one might ask, is argumentation worthy of our attention in education
and educational technology? Does it hold the importance of more traditional
targets of educational technology, such as mathematics and science? The legal
scenario above is a good example of the challenges of learning argumentation, yet
how many students aim to become lawyers? The answer to this is that
argumentation skills are not specific to professions like the law. In fact,
iv
argumentation skills are critical for humans in many aspects of life, both
personally and professionally. Some researchers have even characterized
argumentation skills as central to thinking itself, supporting people in coming to
rational conclusions about issues as varied as gun laws, the responsibilities of
countries and individuals in addressing global climate change, and why children
in some nations appear to learn more than in other nations. Put simply,
argumentation, while very difficult to teach and learn, is clearly an important skill
to pass on to the masses in assuring a civilized, well-educated society.
Often, human teachers provide instruction on argumentation through face-to-face
dialog and direct interaction with students. Sometimes students can even get one-
on-one tutoring, an approach that has been shown to be the most effective form of
instruction. Yet, while classroom learning and one-on-one tutoring are likely the
best ways for students to learn to argue, it is difficult, if not impossible, to “scale
up” such approaches, teaching large numbers of students effectively, due to
limitations in teacher/tutor time and availability. If educational technology can be
brought to bear, then instruction on argumentation, at a large scale, might be
realized.
In recent years researchers have investigated the use of educational technologies
for teaching argumentation. This volume, which is partially based on a workshop
on educational argumentation technologies that was held in conjunction with
Computer Supported Collaborative Learning (CSCL) 2009 in Rhodes, Greece,
reflects some of this work. The authors of the chapters present a collection of
current State-of-the-Art approaches in educational technologies for
argumentation, both individual and collaborative use systems. The e-Book begins
with chapters that present more conceptual and foundational work, aimed at
ultimately providing tools that will help the field of educational technology in
evaluating argumentation and argumentation tools. De Ascaniis suggests criteria
to design and evaluate argument diagramming tools from the point of view of
argumentation theory (chapter 1). Theorists such as Wigmore, Toulmin, Van
Eemeren & Grootendorst provide the foundation for De Ascaniis’ criteria, and she
focuses on evaluating argument diagramming tools both from the perspective of
sound argumentation and how to communicate those arguments in interacting
with and influencing people in the real world. Sionti and colleagues pick up on De
v
Ascaniis’ theme of how arguments are communicated by evaluating actual
classroom discussions and the patterns that emerge (chapter 2). They use and
extend an existing analysis approach that, they hope, will soon be capable of
doing automated analysis of such classroom talk. These two foundational chapters
are then followed by two State-of-the-Art chapters that provide the reader with
information about the state of argument technologies. Dowell provides an
overview of collaborative visual argumentation tools, in particular, looking at how
such tools have been evaluated for their effects on learning and collaboration
(chapter 3). The Dowell chapter picks up on De Ascaniis’ focus on argument
diagramming – a technique that is oft used and explored in this area of research –
yet more from an analytic viewpoint – how have argument diagramming tools
been evaluated until now? – and less from a prescriptive viewpoint, as De
Ascaniis does. Dowell raises the significant distinction between evaluating
acquisition (i.e., how much knowledge has been gained?) and participation (i.e.,
how much have the students engaged in productive conversation?). These two
strands of analysis have been central to the evaluation of argumentation systems,
in general, with different researchers emphasizing one approach or the other.
Scheuer and colleagues, on the other hand, provide an overview of argument
analysis and intelligent feedback (chapter 4). As opposed to Dowell’s review,
which focuses on less interactive systems, Scheuer et al., report on past work that,
for instance, attempts to use artificial intelligence techniques, such as machine
learning and text mining, to evaluate the content of arguments and to provide
some feedback or help to the student. While in-roads have been made in this area
of educational technology for argumentation, it is also made clear by Scheuer et
al., that there are many challenges ahead, such as the fact that adaptive systems –
those that can track and react to the actions of students – are not nearly reliable
enough yet to be used in practice. The remainder of the e-Book (chapters 5-10)
describes systems that are targeted at different aspects of argumentation, in
different domains. Unlike the Dowell and Scheuer et al., chapters, these chapters
go deeper into specific work, providing the reader with, effectively, case studies
of modern systems for learning argumentation. In chapter 5 De Chiara, Manno,
and Scarano present the CoFFEE (Collaborative Face to Face Educational
Environment) framework, an open software environment for incorporating a
variety of collaborative tools. The contribution of this software is that it provides a