Capturing the Sequential Pattern of Students’ Interactions in Computer-Supported Collaborative Learning

Abstract

The computer-supported collaborative learning (CSCL) has gained significant popularity in sharing knowledge and problem solving. The present study aims to capture the temporal interactions of dental students in online problem-based learning (PBL). The dataset consisted of 1,265 posts from 68 students subjected to coding and analysis using process and sequence mining approaches. The non-argument discussion was the most prevalent interaction, followed by knowledge sharing, social interactions, and argumentation. Process mining demonstrated the dynamics of student engagement, which started with knowledge sharing that led to argumentation, discussion, and eventual evaluation. Social interactions played a significant role in improving collaborative learning and knowledge construction. Sequence mining clustered student interactions into three groups: Argumentation, Non-Argumentation, and Critical Thinking. Each group exhibited unique engagement pattern, with different starting points and subsequent interactions. In conclusion, process and sequence mining utilization can identify the different phases of collaborative interactions in CSCL. It may offer implications for teachers to facilitate effective discussion and create a better online learning experience. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.