Computer-supported collaborative learning

Computer-supported collaborative learning (CSCL) is a pedagogical approach wherein learning takes place via social interaction using a computer or through the Internet. This kind of learning is characterized by the sharing and construction of knowledge among participants using technology as their primary means of communication or as a common resource. CSCL can be implemented in online and classroom learning environments and can take place synchronously or asynchronously. The study of computer-supported collaborative learning draws on a number of academic disciplines, including instructional technology, educational psychology, sociology, cognitive psychology, and social psychology. It is related to collaborative learning and computer supported cooperative work (CSCW). History Interactive computing technology was primarily conceived by academics, but the use of technology in education has historically been defined by contemporary research trends. The earliest instances of soft

Peer knowledge modeling in computer supported collaborative learning

Mirweis Sangin

Learners benefit from collaboration because it triggers effective interaction processes such as externalization, elicitation and negotiation of knowledge. In order to communicate effectively, learners need to have a certain representation of their peers' knowledge. We refer to the process of building and maintaining a representation of the peers' knowledge as peer knowledge modeling. The present thesis aim at making contributions to the fields of computer support collaborative learning and work (CSCL, CSCW) on three main levels. First, as an empirical contribution, we investigate the process of peer knowledge modeling in the context of CSCL. Our main research question inquires the effects of a socio-cognitive support, providing co-learners with cues about their peer's prior knowledge, on collaborative learning outcomes and processes. In an empirical study (the KAT experiment), university students (N=64) participated in a remote computer-mediated dyadic learning scenario. They were provided (or not) with a visual representation of their partner's prior-knowledge level through a Knowledge Awareness Tool (KAT). Results showed that the KAT enhances co-learners' collaborative learning gain. This effect appears to be mediated by the positive effect of the KAT on participants' accuracy in estimating their peer's knowledge. Analyses on the process level showed that participants of the KAT condition produce more elaborated utterances. KAT condition dyads' interactions are more focused on knowledge negotiation, whereas the control condition dyads are mainly focused on task completion. The KAT seems to provide a sensitizing metacognitive support, structuring and regulating the collaboration by helping co-learners to cope with their knowledge gaps and discrepancies. Second, as a methodological contribution, we examine the affordance of dual eye tracking techniques as an innovative methodology to investigate, on a deeper level, the socio-cognitive processes underlying collaboration. We introduce DUET (DUal Eye-Tracking), a method using a multimodal technique to collect rich data featuring peers' synchronized gaze patterns, verbal interaction and potentially activities. We examine the main research applications of DUET and exemplify them with analyses conducted in the context of the KAT experiment. DUET method appears to be a promising technique to investigate collaborative processes on a deep level. Finally, as a third computational contribution, we built upon micro-level analyses of the verbal referencing process to introduce and test REGARD, a computational model allowing to automatically detect verbal references and locate the specific object of reference. The results of the test show a reasonably good accuracy of the REGARD algorithm to detect and associate verbal references to objects of reference. We discuss the design and research application of the REGARD model for the field of CSCL, CSCW and more generally HCI.

EPFL2009

The effects of animations on verbal interaction in computer supported collaborative learning

Pierre Dillenbourg, Gaëlle Molinari, Mirweis Sangin

This paper focuses on the interaction patterns of learners studying in pairs who were provided with multimedia learning material. In a previous article, we reported that learning scores were higher for dyads of an ‘animations’ condition than for dyads of a ‘static pictures’ condition. Results also showed that offering a persistent display of one snapshot of each animated sequence hindered collaborative learning. In the present paper, further analyses of verbal interactions within learning dyads were performed in order to have a better understanding of both the beneficial effect of animations and the detrimental effect of the presence of persistent snapshots of critical steps on collaborative learning. Results did not show any differences in terms of verbal categories between the two versions of the instructional material, that is, static versus animated pictures. Pairs who were provided with persistent snapshots of the multimedia sequences produced fewer utterances compared to participants without the snapshots. In addition, the persistent snapshots were detrimental both in terms of providing information about the learning content and in terms of producing utterances solely for the purpose of managing the interaction. In this study, evidence also showed that these two verbal categories were positively related to learning performances. Finally, mediation analyses revealed that the negative effect of persistent snapshots was mediated by the fact that peers of the snapshots condition produced less information providing and interaction management utterances. Results are interpreted using a psycholinguistic framework applied to computer-supported collaborative learning (CSCL) literature and general guidelines are derived for the use of dynamic material and persistency tools in the design of CSCL environments.

2008

Knowledge interdependence with the partner, accuracy of mutual knowledge model and computer-supported collaborative learning

Pierre Dillenbourg, Gaëlle Molinari, Mirweis Sangin

The present study is part of a project aiming at empirically investigating the process of modeling the partner’s knowledge (Mutual Knowledge Modeling or MKM) in Computer-Supported Collaborative Learning (CSCL) settings. In this study, a macro-collaborative script was used to produce knowledge interdependence (KI) among colearners by providing them with different but complementary information. Prior to collaboration, two students read the same text in the “Same Information” (SI) condition while each of them read one of two complementary texts in the “Complementary Information” (CI) condition. After the collaboration phase, a knowledge modeling questionnaire asked participants to estimate both their own — and their partner’s outcome knowledge thanks to Likert-type scales. The relation between the accuracy with which co-learners assess their partner’s knowledge and learning has been examined. In addition, we investigated the KI effect on (a) learning performance and (b) the MKM accuracy. Finally, we wondered to what extent the MKM accuracy could mediate the KI effect on learning. Results showed no difference in learning performance between participants who worked on same information and participants who worked on complementary information. We also found that participants were more accurate at assessing their partner’s knowledge in the SI condition than in the CI condition. The discussion focuses on methodological limitations and provides new directions for investigating the KI effect on MKM accuracy.

2009

Peer knowledge modeling in computer supported collaborative learning

Mirweis Sangin

EPFL2009