This paper reports on results of applying process discovery mining and sequence classification mining techniques to a data set of semi-structured learning activities. The main research objective is to advance educational data mining to model and support self-regulated learning in heterogeneous environments of learning content, activities, and…

Instructional strategies can be helpful in facilitating students' knowledge construction and developing advanced cognitive skills. In the context of collaborative learning, instructional strategies as scripts can guide learners to engage in more meaningful interaction. Previous studies have been investigated the benefits of different instructional…

This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…