Modeling group process in collaborative learning and problem-solving using agent-based simulation

Published: 21 June 2021| Version 2 | DOI: 10.17632/wx9rrt7kr6.2
Yue Ma,


Understanding how collaborative groups accomplish their work is a complex undertaking, because group problem-solving is a dynamic process, affected by interactions among many factors including the team’s tasks and goals, the prior skills and capabilities of its individual members, the communication and social dynamics between members, and other aspects of the task and the working environment. In educational contexts an additional crucial question arises: What is the relationship of group performance to individual learning outcomes, and how do group process mechanisms determine that relationship? Also, a critical task variable, discussed in the literature but little studied, is the demonstrability of the correct solution (Shaw, 1963); we investigate its role in moderating learning and performance outcomes. To investigate these questions, we propose a model of how group process facilitates individual learning and task performance in groups, and adopt a simulation approach employing agent-based modeling to assess the importance of and interactions among factors hypothesized to affect group problem-solving process, performance outcomes, and individual learning. Our simulation incorporates a simple cognitively diagnostic measurement model relating prior knowledge and learned skills to performance, a framework that offers conceptual advantages in modeling prior task-relevant knowledge, the demonstrability of correct solutions, individual learning, and process gains from the group work.



Teachers College of Columbia University


Agent-Based Modeling, Cooperative Learning, Problem Solving, Collaborative Education