This study explores the potential of using screen time data in learning management systems (LMS) to estimate student learning time (SLT) and validate the credit value of courses. Gathering comprehensive data on actual student learning time is difficult, so this study uses LMS Moodle logs from a computer programming course with 490 students over 16 weeks to estimate SLT. The data was segmented into a minute for each record and total duration was calculated for each student on a weekly basis. The study found variations in SLT on a weekly basis and identified that the number of students who engaged with the LMS after midnight varied according to week, possibly due to assessment deadlines. These findings suggest that screen time data in LMS can be utilized for data-driven decision making for academic quality assurance in higher education. This study can help policy makers and academic institutions to make more informed decisions and promote personalized learning experiences. [For the full proceedings, see ED654100.]