Factors and conditions that affect the goodness of machine learning models for predicting the success of learning címmel jelent meg Bognár László és Fauszt Tibor írása, a Computers and Education: Artificial Intelligence folyóiratban.
Absztrakt:
The process for building effective machine learning models that predict the learning success of university students, the competencies of the actors involved in model building, and the main factors and conditions that influence the reliability of the predictions are reviewed in this paper. It is shown that, in addition to the site-level and course-level indicators commonly used in the literature for prediction, significantly more accurate predictions can be made by introducing so-called chapter-level indicators. These chapter-level indicators are closely linked to the content structure of the subject under study, the hierarchy of its chapters and the learning resources and student activities used in them.
Gratulálunk a szerzőknek!