Uncovering Patterns in Constructionist Collaborative Learning Activities via Cluster Analysis of Museum Exhibit Log Files

• In Event: Computer-Supported Collaborative Learning

Abstract

A driving factor in designing interactive museum exhibits to support simultaneous users is that visitors learn from one another, via both observation and conversation. Such collaborative interactions among museum-goers are typically analyzed through manual coding of live- or video-recorded exhibit use. We sought to determine how log data from an interactive multi-user exhibit could indicate patterns in visitor interactions that could shed light on informal collaborative constructivist learning. We characterized patterns from log data generated by an interactive tangible tabletop exhibit using factors like "pace of activity" and the timing of “success events." Here we describe processes for parsing and visualizing log data and explore what these processes revealed about individual and group interactions with interactive museum exhibits.

Authors

• Natalie Jorion, Pearson VUE

• Jessica Roberts, Carnegie Mellon University

• Alex J. Bowers, Teachers College, Columbia University

• Mike Tissenbaum, Massachusetts Institute of Technology

• Leilah Lyons, University of Illinois at Chicago

• Vishesh Kumar, University of Wisconsin - Madison

• Matthew Berland, University of Wisconsin - Madison