Abstract
We researched the possibility of predicting the final grades of university students with the help of online course management systems. By using the activity logs from the system we identify those variables that could be used during predictions. We experimentally narrowed-down the selection to two variables that would be useful for constructing linear regression models for grade prediction. The identified variables were the number of specific activities and the intermediate grades of the students. An experiment was conducted in order to evaluate the selection regarding five courses, which would show whether these two variables could help build a prediction model with accuracy of up to 91.7 % for a given course.
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Černezel, A., Karakatič, S., Brumen, B., Podgorelec, V. (2014). Predicting Grades Based on Students’ Online Course Activities. In: Uden, L., Fuenzaliza Oshee, D., Ting, IH., Liberona, D. (eds) Knowledge Management in Organizations. KMO 2014. Lecture Notes in Business Information Processing, vol 185. Springer, Cham. https://doi.org/10.1007/978-3-319-08618-7_11
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