Internal and external collaboration scripts in web-based science learning at schools

Kollar, Ingo; Fischer, Frank; Slotta, James D.

doi:10.3115/1149293.1149336

Cited by 45 publications

(57 citation statements)

References 25 publications

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“…Collaboration scripts may focus on specific aspects of collaboration (Kollar et al 2005;O'Donnell and Dansereau 1992;Stegmann et al 2007). In this way, computer-supported collaboration scripts may apply on specific dimensions of argumentative knowledge construction.…”

Section: Linguistic Inquiry and Word Count (Liwc)mentioning

confidence: 99%

Analyzing collaborative learning processes automatically: Exploiting the advances of computational linguistics in computer-supported collaborative learning

Rosé

Wang

Cui

et al. 2008

Computer Supported Learning

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163

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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.

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Section: Linguistic Inquiry and Word Count (Liwc)mentioning

confidence: 99%

Analyzing collaborative learning processes automatically: Exploiting the advances of computational linguistics in computer-supported collaborative learning

Rosé

Wang

Cui

et al. 2008

Computer Supported Learning

Self Cite

250

163

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“…Pifarré and Cobos (2009) present empirical evidence from a qualitative study suggesting that their tool supports the development of metacognitive knowledge. Also Kollar, Fischer, and Slotta (2005) and Fisher, Kollar, Haake, and Mandl (2007) summarize a number of CSCL-studies that underpin the potential of scripts to foster metacognition.…”

Section: Discussionmentioning

confidence: 99%

Supporting active cognitive processing in collaborative groups: The potential of Bloom's taxonomy as a labeling tool

Valcke

Wever

Zhu

et al. 2009

The Internet and Higher Education

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“…Several studies could substantiate the superiority of this approach compared to respective controls (e.g. [17][18][19]). …”

Section: B Usability-a Tradeoff Between Economy Of Effortmentioning

confidence: 99%

Enhancing the Digital Backchannel Backstage on the Basis of a Formative User Study

Pohl

Gehlen-Baum

Bry

2012

Int. J. Emerg. Technol. Learn.

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Abstract-Contemporary higher education with its large audiences suffers from passivity of students. Enhancing the classroom with a digital backchannel can contribute to establishing and fostering active participation of and collaboration among students in the lecture. Therefore, we conceived the digital backchannel Backstage specifically tailored for the use in large classes. At an early phase of development we tested its core functionalities in a smallscale user study. The aim of the study was to gain first impressions of its adoption, and also to form a basis for further steps in the conception of Backstage. Regarding adoption we particularly focused on how Backstage influences the participants' questioning behavior, a salient aspect in learning. We observed that during the study much more questions were uttered on Backstage than being asked without backchannel support. Regarding the further development of Backstage we capitalized on the participants' usability feedback. The key of the refinement is the integration of presentation slides in Backstage, which leads to an interesting reconsideration of the user interactions of Backstage. This article is a reworked and extended version of the authors' submission for the International Conference ICL 2011.

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Internal and external collaboration scripts in web-based science learning at schools

Cited by 45 publications

References 25 publications

Analyzing collaborative learning processes automatically: Exploiting the advances of computational linguistics in computer-supported collaborative learning

Analyzing collaborative learning processes automatically: Exploiting the advances of computational linguistics in computer-supported collaborative learning

Supporting active cognitive processing in collaborative groups: The potential of Bloom's taxonomy as a labeling tool

Enhancing the Digital Backchannel Backstage on the Basis of a Formative User Study

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