Agent-mediated self-regulated learning: A conceptual model based on knowledge management at agent level

Continuous improvement and self-regulation are often mentioned when a person talks about quality of education or teaching and learning. In 1990s, the concept of self-regulated learning (SRL) came into picture to describe the need for learners to consistently improve their study method, and it was seen cited again in recent years due to the emergence of new technologies that have opened more windows to the learners to improve their studies. Nevertheless, there is a gap in the research on knowing who is performing the SRL and who is not. This has brought into the attention of presenting this paper on knowing what a learner is doing, using software agents to intelligently trace the learners' online learning activities. The purpose of this paper is to conceptualise an idea of having software agents to mediate the tasks of the learners, by performing personal knowledge management (PKM) processes at agent level. The expected outcome is a conceptual model of agents' interaction with their environment, and how to analyse the information or knowledge retrieved from the sources in order to provide a better report to their learners for their benefit of SRL.