Application of Learning Analytics to Differentiate Video-Based Learning Environments

This research aimed to investigate the impact of differentiated video-based learning (VBL) compared to conventional VBL on learning, self-regulation learning (SRL), and satisfaction with the course with an innovative pedagogical approach. Given the critical importance of addressing diverse learner needs and characteristics in online educational environments, particularly in an era increasingly dominated by digital tools, the potential of learning analytics (LA) to meet these challenges merits rigorous investigation. This research employed a quasi-experimental design, utilizing a pre-test-post-test model with control groups. A total of sixty teachers, selected via convenience sampling, were randomly allocated to either the experimental or control groups. Data were gathered using several instruments: an online SRL questionnaire, a bespoke learning assessment, and a course satisfaction survey, and the LA tool. The instructional intervention, comprising a five-session course on the subject of principles of instructional design, was administered with LA support in differentiated form for the experimental group and without for the control group. Both descriptive and inferential statistical methods were used to analyze the data. The results indicated that the experimental group, which engaged in the differentiated VBL approach, showed significantly greater improvements in learning outcomes, SRL, and overall satisfaction compared to the control group, which received conventional VBL. Based on the results, suggestions were discussed.