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Updated: Nov 7, 2025

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
Published on: June 10, 2021
Using learning management software data to compare students' actual and self-reported viewing of video lectures
JoAnna M Scott1, Brenda S Bohaty2,3, Cynthia C Gadbury-Amyot4
1Office of Research and Graduate Program, School of Dentistry, University of Missouri-Kansas City, Kansas City, Missouri, USA.
Purpose:
Student engagement is typically measured by class attendance and questionnaires. Learning management systems (LMS) provide additional sources of objective data that can evaluate student performance. This study compared dental students' self-report of course video viewing with LMS data.
Methods:
Dental students in a 2018 flipped pediatric dentistry course were given a questionnaire after course completion that captured self-reported course video viewing. Student data and time spent on videos were extracted from the LMS and matched to the questionnaire. McNemar's test evaluated differences between self-reported and matching LMS data.
Results:
Of the 109 enrolled students, 99 (91%) completed the questionnaire. Most students self-reported that they watched more than half of the videos (71%), re-watched at least once (89%), and watched at times other than 8 a.m.-5 p.m. (80%). Of the 104 students with data from the LMS, 40% of students watched more than half of the videos, 49% re-watched at least one video, and 60% watched between 8 a.m.-5 p.m. LMS data showed 14 (13%) students did not watch any videos. Significant differences were found between self-reported video viewing and matched LMS video data in (1) percentage of videos watched, (2) number of times videos were re-watched, and (3) most frequent time for watching the videos (p < 0.001 for all).
Conclusion:
Technology is a tool that helps instructors more accurately track students' study habits compared to observation or self-report. When evaluating time spent watching videos via an LMS, students tend to overestimate the amount of viewing time.
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