Collaborative Learning / Edition 1

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Overview

Collaborative Learning: Cognitive and Computational Approaches is one of the outcomes of the European Science Foundation's research programme on "Learning in Humans and Machines". It will be of interest to a wide audience of researchers and students in the fields of education, psychology, communication sciences and computer science, as well as the fast growing community of people who investigate how the Internet may be used in education and training.

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 collaborative learning 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 in computer science to describe the interactions among artificial agents. The term has often been used rather loosely in the different research communities: this book is a contribution towards refining and operationalizing the concept

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Product Details

  • ISBN-13: 9780080430737
  • Publisher: Emerald Group Publishing
  • Publication date: 2/17/1999
  • Series: Advances in Learning and Instruction Series
  • Edition description: 1 ED
  • Edition number: 1
  • Pages: 260
  • Product dimensions: 6.14 (w) x 9.21 (h) x 0.63 (d)

Table of Contents

Acknowledgement
Contributors
1 Introduction: What Do You Mean By "Collaborative Learning"? 1
2 Learning Together: Understanding the Processes of Computer-Based Collaborative Learning 20
3 The Role of Grounding in Collaborative Learning Tasks 31
4 What is "Multi" in Multi-agent Learning? 64
5 Comparing Human-Human and Robot-Robot Interactions 81
6 Learning by Explaining to Oneself and to Others 103
7 Knowledge Transformations in Agents and Interactions: A Comparison of Machine Learning and Dialogue Operators 122
8 Can Analytic Models Support Learning in Groups? 147
9 Using Telematics for Collaborative Knowledge Construction 169
10 The Productive Agency that Drives Collaborative Learning 197
References 219
Index 243
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