Modeling and predicting students' engagement behaviors using mixture Markov models

arXiv:2403.05556v1 Announce Type: cross
Abstract: Students' engagements reflect their level of involvement in an ongoing learning process which can be estimated through their interactions with a computer-based learning or assessment system. A pre-requirement for stimulating student engagement lies in the capability to have an approximate representation model for comprehending students' varied (dis)engagement behaviors. In this paper, we utilized model-based clustering for this purpose which generates K mixture Markov models to group students' traces containing their (dis)engagement behavioral patterns. To prevent …

abstract arxiv assessment capability computer cs.cy cs.lg engagement interactions lies markov modeling process representation students through type