Classification of Learning Patterns and Outliers Using Moodle Course Material Clickstreams and Quiz Scores

Abstract

In this study, learning patterns and outliers were classified using learning logs in Moodle, and a method was proposed to identify learners who were struggling in class based on the relationship between learning patterns and outliers. The proposed method utilizes the deviation between the learner’s course material clickstream and the quiz score accumulated in Moodle to classify the learner into one of four learning patterns. As the number of lessons increased, many learners transitioned through four learning patterns. However, some of the top or bottom learners on the final quiz score may repeat the same learning pattern, which tends to result in outliers.