Intended to illustrate the benefits of collaboration between scientists from psychology and computer science, namely machine learning, this book contains the following chapters, most of which are co-authored by scholars from both sides: (1) "Introduction: What Do You Mean by 'Collaborative Learning'?" (Pierre Dillenbourg); (2) "Learning Together: Understanding the Processes of Computer-Based Collaborative Learning" (Karen Littleton and Paivi Hakkinen); (3) "The Role of Grounding in Collaborative Learning Tasks" (Michael Baker, Tia Hansen, Richard Joiner, and David Traum); (4) "What Is 'Multi' in Multi-Agent Learning?" (Gerhard Weiss and Pierre Dillenbourg); (5) "Comparing Human-Human and Robot-Robot Interaction" (Richard Joiner, Kim Issroff, and John Demiris); (6) "Learning by Explaining to Oneself and to Others" (Rolf Ploetzner, Pierre Dillenbourg, Michael Preier, and David Traum); (7) "Knowledge Transformations in Agents and Interactions: A Comparison of Machine Learning and Dialogue Operators" (Engelbert Mephu Nguifo, Michael Baker, and Pierre Dillenbourg); (8) "Can Analytic Models Support Learning in Groups?" (H. Ulrich Hoppe and Rolf Ploetzner); (9) "Using Telematics for Collaborative Knowledge Construction" (Tia Hansen, Lone Dirckinck-Holmfeld, Robert Lewis, and Joze Rugelj); and (10) "The Productive Agency that Drives Collaborative Learning" (Daniel L. Schwartz). Contains an index. (Contains 425 references.) (MES)