Sustainable e-Learning by Data Mining—Successful Results in a Chilean University

People are increasingly open to using online education mainly break the distance and time barriers of presential education. This type is sustainable at all levels, its relevance has increased even more during pandemic. Consequently, educational institutions saving large volumes data containing relevant information about their operations, but they do not know why students succeed or fail. The Knowledge Discovery in Databases (KDD) process could support this challenge by extracting innovative models identify main patterns factors that affect success programs. work uses CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology analyze from Distance Education Center Universidad Católica del Norte (DEC-UCN) 2000 2018. was chosen because it represents a proven integrates multiple methodologies provide an effective meta-process knowledge projects. DEC-UCN one first centers implement learning Chile, study analyses 18,610 records period. applies mining, most critical KDD phase, find hidden variables associated with students’ (e-learning) found explaining student e-learning programs age, gender, degree study, level, locality.