Proceedings of CSCL '97: The Second International Conference on Computer Support for Collaborative Learning, December 10-14, 1997, University of Toronto, Toronto, Ontario, Canada

By Rogers Hall; Naomi Miyake et al. | Go to book overview

Integrating and Guiding Collaboration: Lessons Learned in Computer-Supported Collaborative Learning Research at Georgia Tech

Mark Guzdial,* Cindy Hmelo,† Roland Hübscher,* Kris Nagel,* Wendy Newstetter ,* Sadhana Puntambekar,* Amnon Shabo,* Jennifer Turns,§ and Janet L. Kolodner *

* EduTech Institute, College of Computing Georgia Institute of Technology, Learning Research and Development Center University of Pittsburgh, § EduTech Institute, Center for Human-Machine Systems Research, School of Industrial and Systems Engineering, Georgia Institute of Technology


Directions of Progress: Integrating and Guiding

Research on computer-supported collaborative learning at the EduTech Institute at Georgia Tech is relatively new at less than five years old. In that short span, however, the team of researchers has developed eight different prototype software systems and evaluated them in a variety of settings with middle school, undergraduate, and graduate students. In this paper, we reflect on some of the overall lessons learned through this work.

We have developed an approach to instruction that involves students' learning through solving real- world problems. We help students manage the complexity of these problems in several ways. First, we use the methodology from problem-based learning (PBL) to help students structure their problem- solving. Second, we provide students with case libraries to help them learn from the experience of others. Third, we provide support for student reflection. Part of these ideas developed out of the close fit that we saw between the PBL educational methodology and the cognitive model derived from case-based reasoning [1]. Later work has focused on merging what we know about the design process with the PBL classroom methodology.

In PBL, students learn by solving authentic real- world problems and reflecting on their experiences. For example, engineering students learn how to design as they try to design kites and kiosks. Because these problems are complex, students work in groups, where they pool their knowledge and together grapple with the issues that must be considered. Facilitators guide student reflection on their problem-solving experiences, asking students to articulate both the concepts and skills they are learning, those they still need to learn more about and helping them identify the strategies needed for problem solving, collaboration, and self-directed learning.

Case-based reasoning (CBR) refers to reasoning based on previous experiences [2]. It might mean solving a new problem by adapting an old solution or merging pieces of several old solutions, interpreting a new situation in light of similar situations, or projecting the effects of a new situation by examining the effects of a similar old situation. Learning, in the CBR paradigm, means extending one's knowledge by incorporating new experiences into memory, by re- indexing old experiences to make them more accessible, and by abstracting out generalizations

____________________
*
EduTech Institute, College of Computing Georgia Institute of Technology 801 Atlantic Drive Atlanta, GA 30332- 0280, {guzdial, roland, kris, wendy, sadhana, amnonh, jlk}@cc.gatech.edu
§
EduTech Institute Center for Human-Machine Systems Research School of Industrial and Systems Engineering Georgia Institute of Technology, jennifer@isye.gatech.edu
Learning Research and Development Center University of Pittsburgh, hmelo@pop.pitt.edu

-91-

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