| User Behavioral Patterns and Early Dropouts Detection: Improved Users Profiling through Analysis of Successive Offering of MOOC. M Vitiello, S Walk, D Helic, V Chang, C Guetl J. Univers. Comput. Sci. 24 (8), 1131-1150, 2018 | 41 | 2018 |
| MOOC dropouts: A multi-system classifier M Vitiello, S Walk, V Chang, R Hernandez, D Helic, C Guetl Data Driven Approaches in Digital Education: 12th European Conference on …, 2017 | 26 | 2017 |
| Classifying students to improve MOOC dropout rates M Vitiello, S Walk, R Hernández, D Helic, C Gütl Research Track 501, 2016 | 10 | 2016 |
| MOOC learner behaviour: attrition and retention analysis and prediction based on 11 courses on the TELESCOPE platform M Vitiello, C Gütl, HR Amado-Salvatierra, R Hernández Learning Technology for Education Challenges: 6th International Workshop …, 2017 | 9 | 2017 |
| Predicting dropouts on the successive offering of a MOOC M Vitiello, S Walk, D Helic, V Chang, C Gütl Proceedings of the 2017 International Conference MOOC-Maker, MOOC-Maker 2017 …, 2017 | 4 | 2017 |
