Learner modeling is a basis of personalized, adaptive learning. The research literature
provides a wide range of modeling approaches, but it does not provide guidance for …

Simulation is a powerful approach that plays a significant role in science and technology.
Computational models that simulate learner interactions and data hold great promise for …

Artificial intelligence (AI) applications continue to improve decision-making processes at all
levels of education. A relatively untouched area in which AI can be quite useful is …

Capturing students' behavioral patterns through analysis of sequential interaction logs is an
important task in educational data mining and could enable more effective and personalized …

The widespread use of temporal aspects in user modeling indicates their importance, and
their consideration showed to be highly effective in various domains related to user …

Recent advancements in the collection and analysis of sequential educational data have
brought time series analysis to a pivotal position in educational research, highlighting its …

Educational software data promises unique insights into students' study behaviors and
drivers of success. While much work has been dedicated to performance prediction in …

Pupil absenteeism remains a significant problem for schools across the globe with negative
impacts on overall pupil performance being well-documented. Whilst all schools continue to …

Students' interactions with online tools can provide us with insights into their study and work
habits. Prior research has shown that these habits, even as simple as the number of actions …

The analysis of log data generated by online educational systems is an important task for
improving the systems, and furthering our knowledge of how students learn. This paper uses …