Evaluating learning style-based grouping strategies in real-world collaborative learning environment

Abstract

Collaborative learning is defined as situations where multiple learners participate in solving common problems. Collaborative learning provides a way of building knowledge through activities of collaboration with others. Group work is a representative form of collaborative learning and has been used in higher education. In group work, however, one of the widely discussed issues is group composition. Students have different attributes including learning styles, background knowledges, gender, and so on. Typical group formations are homogeneous and heterogeneous compositions. Numerous work addressed the problem and evaluated how learning outcome varies between different group formations both in online and physical environments. In this study, we focus on the group formation for real-world collaboration. We introduce different types of grouping into a class of a theme-based course and discuss the effects of different learning styles in collaborative learning environment. Students are characterized according to Kolb’s learning style inventory and then grouped by homogeneous, heterogeneous, and random strategies. We investigate how intra-group interactions varies with different types of composition; we monitor the activity levels of every group and have students peer-review each other for quantitative evaluation of contributions. We find typical patterns of activities and contributions, and discuss their association to grouping strategies.