Process Modeling of Log and Discourse Data to Understand Collaborative Inquiry in Engineering Problem-Solving

• In Event: Computational Analyses of STEM+C Learning

Abstract

To train engineering practice and develop conceptual model in engineering education, collaborative inquiry allows peer discussion during joint inquiry that can offer new affordances to facilitate engineering problem-solving performance. However, the dynamic and complex interactions between group members, and between human and computer simulation environment in collaborative inquiry deserve a more nuanced investigation. To better understand learners’ behavior in collaborative inquiry process, this study adopted process mining approach to compare cognitive and social patterns of high and low performing dyads when solving a fluid mechanics problem in an undergraduate course by analyzing log and discourse data. The findings indicated different learning patterns of productive and unproductive groups in terms of problem-solving behavior and cognitive and social processes in problem-solving discourse.

Authors

• Bian Wu, East China Normal University

• Zhenping Yan, East China Normal University

• Chengjun Feng, East China Normal University

• Yanyan Sun, East China Normal University