The use of learning management systems (LMS) in education make it possible to track students’ online behavior. This data can be used for educational data mining and learning analytics, for example, by predicting student performance. Although LMS data might contain usefu... View more
Bipp, T., K. A. and S. Schinkel 2013. Bachelor entrance study (BEST), onderzoek naar studiesucces en drop-out binnen de bachelor opleidingen aan de faculteit industrial engineering & innovation sciences aan de TU/e. Technical report, Eindhoven University of Technology.
Britton, B. K. and A. Tesser 1991. Effects of time-management practices on college grades. Journal of educational psychology, 83(3):405.
Campbell, J. P., D. G. Oblinger, et al. 2007. Academic analytics. Educause Quarterly, Pp. 1-20.
Clow, D. 2013. An overview of learning analytics. Teaching in Higher Education, 18(6):683-695.
Conard, M. A. 2006. Aptitude is not enough: How personality and behavior predict academic performance. Journal of Research in Personality, 40(3):339-346.
Conijn, R., C. Snijders, A. Kleingeld, and U. Matzat 2017. Predicting student performance from LMS data: A comparison of 17 blended courses using Moodle LMS. (in press).
Cortez, P. and A. M. G. Silva 2008. Using data mining to predict secondary school student performance. In Proceedings of 5th FUture BUsiness TEChnology Conference, Pp. 5-12. EUROSIS.
Denissen, J. J., R. Geenen, M. A. Van Aken, S. D. Gosling, and J. Potter 2008. Development and validation of a dutch translation of the big five inventory (bfi). Journal of personality assessment, 90(2):152-157.
Dollinger, S. J., A. M. Matyja, and J. L. Huber 2008. Which factors best account for academic success: Those which college students can control or those they cannot? Journal of research in Personality, 42(4):872-885.
Guay, F., R. J. Vallerand, and C. Blanchard 2000. On the assessment of situational intrinsic and extrinsic motivation: The situational motivation scale (sims). Motivation and emotion, 24(3):175-213.