Agent-based Self-regulated Learning Simulation Adopting the Concept of GUSC Model

摘要

The significance of self-regulated learning (SRL) among university students have caught the attention of recent research. A recent research has produced SRL process mapping but the research was limited to producing a simulation video from historical data to prove the occurrence of SRL processes in online learning management system. This paper proposes to extend that research by adopting the concept of personal knowledge management (PKM) using the GUSC Model, to design an agent-based SRL simulation. This would enable real-time data to be analysed as and when it is needed for prediction of SRL activities. The design of the multi-agent system is possible with the availability of data and knowledge on how these data could be interpreted by the software agents to present an SRL process in both graphical and text report forms. This paper presents the process of analysing students' online SRL behaviour throughout a semester, taking into account a technical course as the benchmark case study, and designing the agent- based simulation for lecturers' prediction on students' online SRL behaviour. In order to do so, simulation video from the recent work is analysed to capture moment-to-moment SRL processes. The purpose of this analysis is mainly to facilitate the understanding of how software agents could be animated step by step. The results from this study is expected to be beneficial to the stakeholders of online education system. Future work will be on developing the agent-based simulation of SRL.