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…

Family-School Partnerships (FSP) are important for students' academic achievements and social-emotional development. Therefore, pre-service teachers need to learn how to establish this. However, in teacher education programmes this topic is insufficiently addressed partially attributed to already overloaded programmes. This study reports on a…

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…

The Program for Learning in Accordance with Needs (PLAN) was devised to be self-improving through a system of computer analysis of student performance data. The PLAN instructional program consists of teaching-learning units in various subject areas, such as reading and science, which are composed of self-paced alternative learning activities,…