Collaborative Learning: Cognitive and Computational Approaches by P. DillenbourgCollaborative Learning: Cognitive and Computational Approaches by P. Dillenbourg

Collaborative Learning: Cognitive and Computational Approaches

byP. Dillenbourg

Hardcover | February 17, 1999

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Research on collaborative learning is currently a very popular topic in education, psychology and computer science. In recent years, educational research has attempted to determine under what circumstances collaborativelearning is more effective than learning alone, and more recently, numerous studies have focused on computer-mediated collaborative learning.In psychology, interest in collaborative learning is related to the emergence of new theories such as 'shared cognition' and 'distributed cognition'. These theories move away from the view traditionally held in cognitive science according to which human cognition is bound inside individual heads. The word 'collaboration' is also used very frequently incomputer science to describe the interactions among artificial agents. Theterm has often been used rather loosely in the different research communities: this book is a contribution towards refining and operationalizing the concept.
Title:Collaborative Learning: Cognitive and Computational ApproachesFormat:HardcoverDimensions:9.41 × 7.24 × 0.98 inPublished:February 17, 1999Publisher:PERGAMON PRESS INC.Language:English

The following ISBNs are associated with this title:

ISBN - 10:0080430732

ISBN - 13:9780080430737

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Table of Contents

Acknowledgement. Contributors. Introduction: what do you mean by 'collaborative learning'? (P. Dillenbourg). Learning together: understanding the processes of computer-based collaborative learning (K. Littleton, P. Häkkinen). The role of grounding in collaborative learning tasks (M. Baker et al.). What is "multi" in multi-agent learning? (G. Weiss, P. Dillenbourg). Comparing human-human and robot-robot interactions (R. Joiner et al.). Learning by explaining to oneself and to others (R. Ploetzner et al.). Knowledge transformations in agents and interactions: a comparison of machine learning and dialogue operators (E. Mephu Nguifo et al.). Can analytic models support learning in groups? (H.U. Hoppe, R. Ploetzner). Using telematics for collaborative knowledge construction (T. Hansen et al.). The productive agency that drives collaborative learning (D. Schwatrtz). References. Index.

Editorial Reviews

Ann Jones, The Open University, Milton KeynesThere is no doubt that collaborative learning will continue to be an important area of research for a number of reasons: learning is now viewed as a lifelong activity and increasingly takes place in contexts where learning from interactions with others, whether around technology or through technology, is a vital part of that process. This book plays an important role in documenting and continuing the debate among scientists in two key fields.Computers and Education