Facilitating argumentative knowledge construction with computer-supported collaboration scripts

Online discussions provide opportunities for learners to engage in argumentative debate, but learners rarely formulate well-grounded arguments or benefit individually from participating in online discussions. Learners often do not explicitly warrant their arguments and fail to construct counterarguments (incomplete formal argumentation structure), which is hypothesized to impede individual knowledge acquisition. Computer-supported scripts have been found to support learners during online discussions. Such scripts can support specific discourse activities, such as the construction of single arguments, by supporting learners in explicitly warranting their claims or in constructing specific argumentation sequences, e.g., argument–counterargument sequences, during online discussions. Participation in argumentative discourse is seen to promote both knowledge on argumentation and domain-specific knowledge. However, there have been few empirical investigations regarding the extent to which computer-supported collaboration scripts can foster the formal quality of argumentation and thereby facilitate the individual acquisition of knowledge. One hundred and twenty (120) students of Educational Science participated in the study with a 2×2-factorial design (with vs. without script for the construction of single arguments and with vs. without script for the construction of argumentation sequences) and were randomly divided into groups of three. Results indicated that the collaboration scripts could improve the formal quality of single arguments and the formal quality of argumentation sequences in online discussions. Scripts also facilitated the acquisition of knowledge on argumentation, without affecting the acquisition of domainspecific knowledge

Analyzing collaborative learning processes automatically

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multidimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in

Hypermedia support for argumentation-based rationale: 15 years on from gIBIS and QOC

Having developed, used and evaluated some of the early IBIS-based approaches to design rationale (DR) such as gIBIS and QOC in the late 1980s/mid-1990s, we describe the subsequent evolution of the argumentation-based paradigm through software support, and perspectives drawn from modeling and meeting facilitation. Particular attention is given to the challenge of negotiating the overheads of capturing this form of rationale. Our approach has maintained a strong emphasis on keeping the representational scheme as simple as possible to enable real time meeting mediation and capture, attending explicitly to the skills required to use the approach well, particularly for the sort of participatory, multi-stakeholder requirements analysis demanded by many design problems. However, we can then specialize the notation and the way in which the tool is used in the service of specific methodologies, supported by a customizable hypermedia environment, and interoperable with other software tools. After presenting this approach, called Compendium, we present examples to illustrate the capabilities for support security argumentation in requirements engineering, template driven modeling for document generation, and IBIS-based indexing of and navigation around video records of meetings

Toward a script theory of guidance in computer-supported collaborative learning

This article presents an outline of a script theory of guidance for computer-supported collaborative learning (CSCL). With its four types of components of internal and external scripts (play, scene, role, and scriptlet) and seven principles, this theory addresses the question how CSCL practices are shaped by dynamically re-configured internal collaboration scripts of the participating learners. Furthermore, it explains how internal collaboration scripts develop through participation in CSCL practices. It emphasizes the importance of active application of subject matter knowledge in CSCL practices, and it prioritizes transactive over non-transactive forms of knowledge application in order to facilitate learning. Further, the theory explains how external collaboration scripts modify CSCL practices and how they influence the development of internal collaboration scripts. The principles specify an optimal scaffolding level for external collaboration scripts and allow for the formulation of hypotheses about the fading of external collaboration scripts. Finally, the article points towards conceptual challenges and future research questions

S-COL: A Copernican turn for the development of flexibly reusable collaboration scripts

Collaboration scripts are usually implemented as parts of a particular collaborative-learning platform. Therefore, scripts of demonstrated effectiveness are hardly used with learning platforms at other sites, and replication studies are rare. The approach of a platform-independent description language for scripts that allows for easy implementation of the same script on different platforms has not succeeded yet in making the transfer of scripts feasible. We present an alternative solution that treats the problem as a special case of providing support on top of diverse Web pages: In this case, the challenge is to trigger support based on the recognition of a Web page as belonging to a specific type of functionally equivalent pages such as the search query form or the results page of a search engine. The solution suggested has been implemented by means of a tool called S-COL (Scripting for Collaborative Online Learning) and allows for the sustainable development of scripts and scaffolds that can be used with a broad variety of content and platforms. The tool’s functions are described. In order to demonstrate the feasibility and ease of script reuse with S-COL, we describe the flexible re-implementation of a collaboration script for argumentation in S-COL and its adaptation to different learning platforms. To demonstrate that a collaboration script implemented in S-COL can actually foster learning, an empirical study about the effects of a specific script for collaborative online search on learning activities is presented. The further potentials and the limitations of the S-COL approach are discussed

The Evidence Hub: harnessing the collective intelligence of communities to build evidence-based knowledge

Conventional document and discussion websites provide users with no help in assessing the quality or quantity of evidence behind any given idea. Besides, the very meaning of what evidence is may not be unequivocally defined within a community, and may require deep understanding, common ground and debate. An Evidence Hub is a tool to pool the community collective intelligence on what is evidence for an idea. It provides an infrastructure for debating and building evidence-based knowledge and practice. An Evidence Hub is best thought of as a filter onto other websites — a map that distills the most important issues, ideas and evidence from the noise by making clear why ideas and web resources may be worth further investigation. This paper describes the Evidence Hub concept and rationale, the breath of user engagement and the evolution of specific features, derived from our work with different community groups in the healthcare and educational sector

The Effect of Varied Gender Groupings on Argumentation Skills among Middle School Students in Different Cultures

The purpose of this mixed-methods study was to explore the effect of varied gender groupings on argumentation skills among middle school students in Taiwan and the United States in a project-based learning environment that incorporated a graph-oriented computer-assisted application (GOCAA). A total of 43 students comprised the treatment condition and were engaged in the collaborative argumentation process in same-gender groupings. Of these 43 students, 20 were located in the U.S. and 23 were located in Taiwan. A total of 40 students comprised the control condition and were engaged in the collaborative argumentation process in mixed-gender groupings. Of these 40 students, 19 were in the U.S. and 21 were in Taiwan. In each country, verbal collaborative argumentation was recorded and the students’ post essays were collected. Among females in Taiwan, one-way analysis of variance (ANOVA) indicated that statistically a significant gender-grouping effect was evident on the total argumentation skills outcome, while MANOVA indicated no significant gender-grouping effect on the combined set of skill outcomes. Among females in the U.S., MANOVA indicated statistically significant gender-grouping effect on the combined set of argumentation skills outcomes Specifically, U.S. female students in mixed-gender groupings (the control condition) significantly outperformed female students in single-gender groupings (the treatment condition) in the counterargument and rebuttal skills. No significant group differences were observed among males. A qualitative analysis was conducted to examine how the graph-oriented computer-assisted application supported students’ development of argumentation skills in different gender groupings in both countries. In each country, all teams in both conditions demonstrated a similar pattern of collaborative argumentation with the exception of three female teams in the U.S. Female teams, male teams, (the treatment condition) and mixed-gender teams (the control condition) demonstrated metacognition regulation skills in different degrees and with different scaffolding

Sensemaking on the Pragmatic Web: A Hypermedia Discourse Perspective

The complexity of the dilemmas we face on an organizational, societal and global scale forces us into sensemaking activity. We need tools for expressing and contesting perspectives flexible enough for real time use in meetings, structured enough to help manage longer term memory, and powerful enough to filter the complexity of extended deliberation and debate on an organizational or global scale. This has been the motivation for a programme of basic and applied action research into Hypermedia Discourse, which draws on research in hypertext, information visualization, argumentation, modelling, and meeting facilitation. This paper proposes that this strand of work shares a key principle behind the Pragmatic Web concept, namely, the need to take seriously diverse perspectives and the processes of meaning negotiation. Moreover, it is argued that the hypermedia discourse tools described instantiate this principle in practical tools which permit end-user control over modelling approaches in the absence of consensus