A Heat Map Generation to Visualize Engagement in Classes Using Moodle Learning Logs

In this study, course materials, mainly in the form of PDF files, were uploaded to the Moodle learning management system and face-to-face lessons were conducted. Student clickstreams of the course materials and the results of quizzes were accumulated. The quizzes, which used a 5-alternative format, were prepared from the course materials. Data from the course material clickstreams and the results of the quizzes were analyzed from an educational data mining and learning analytics perspective. A scatter chart and heat map were created to classify students into four groups based on deviations from the average value of clickstreams and quiz scores. The groups were composed of (1) those with high clickstream and high quiz scores, (2) those with low clickstream but high quiz scores, (3) those with low clickstream and low quiz scores, and (4) those with high clickstream but low quiz scores. It is shown that creating a heat map based on an analysis of the results of 13 quizzes and student clickstreams can provide an early indication of student engagement and can be used to signal the need for a corrective intervention in the case of disengaged students.