Role-Based Group Formations and Interactions to Foster Collaboration in Different Classrooms

Abstract

Collaborative learning (CL) is an active learning method that has been shown to improve students' learning. Although the integration of CL in small face-to-face lectures was implemented and evaluated successfully, the implementation within large (e.g., over 200 students) and remote settings is still a subject of research. Challenges such as the goal-oriented group formation of students with spatial or even geographical disparity, or the collaboration itself prevent the actual use. Thus, our goal is to overcome those issues and enable CL in the most diverse classrooms. Therefore, we present a prototype that combines the idea of Audience Response Systems (ARSs), which allow students to participate during the lecture using their mobile devices, with short-term collaborative activities. Based on students' previously given answers, our approach allows the formation of groups using different algorithms and settings. Within these groups, several types of interactions can be defined, e.g., a chat is provided to initiate discussions, or a voting to determine a group answer. The approach is designed to be highly customizable by allowing lecturers to create their individual teaching scenarios based on elements defined in a unified metamodel. All runtime data that is not specified by this model, e.g., the assignment of students to groups, is added using the concept of roles.