The Transition Matrix -- A classification of navigational patterns between LMS course sections
Tobias Hildebrandt, Lars Mehnen
TL;DR
Addresses how students navigate between Moodle course sections and whether course designs support intended navigational flows across courses. The study develops a heatmap-based workflow and a transition-matrix classification to identify dominant navigational patterns at scale (747 courses, ~1.8M events). It introduces a six-metric taxonomy (diagonal strength, blended patterns, dominant sections, entropy) to classify course navigation and compares patterns within and across courses. The approach yields practical guidance for course design, such as leveraging hub sections and arranging content to support diagonal navigation, with implications for blended-learning environments.
Abstract
Learning management systems (LMS) like Moodle are increasingly used to support university teaching. As Moodle courses become more complex, incorporating diverse interactive elements, it is important to understand how students navigate through course sections and whether course designs are meeting student needs. While substantial research exists on student usage of individual LMS elements, there is a lack of research on broader navigational patterns between course sections and how these patterns differ across courses. This study analyzes navigational data from 747 courses in the Moodle LMS at a technical university of applied sciences, representing (after filtering) around 4,400 students and 1.8 million logged events. Transition matrices and heat map visualizations are used to identify and quantify common navigational patterns. Findings include that the majority of the analyzed courses exhibit some kind of diagonal pattern, indicating that students typically navigate from the current to the next or previous section.