AI Summary & Key Takeaways
AI InsightThe optimization of the provision and quality of preferred learning services at the beginning of the semester will be able to avoid higher-risk of non-active students.
📌 3 Key Takeaways
Abstract
The high rate of drop out is still a problem in the distance learning system, including at the Universitas Terbuka (UT). At UT, the term dropout is better known as the status of non-active students. The study aims was to determine the median time and determinant of non-active student in distance learning in Indonesia. This study used a cohort analysis in student of biology department who first registered in 2012 to 2014. The median time of non-active students was identified by the Kaplan-Meier analysis and the determinant of non-active student was analyzed by Cox proportional hazard model. The percentage of non-active students in this study reached 42%, with half of the students becoming non-active in the first two semesters. Students who have a greater risk of becoming non-active are those who are >45 years old, women, employed, recent education is not relevant to the field of biology, knowledge of the concept of distance learning and laboratory practice is lacking, has never participated in online tutorials and face-to-face tutorials, and is not satisfied existing academic services. The optimization of the provision and quality of preferred learning services at the beginning of the semester will be able to avoid higher-risk of non-active students.