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 | 27 | 2018 |
MOOC dropouts: A multi-system classifier M Vitiello, S Walk, V Chang, R Hernandez, D Helic, C Guetl European Conference on Technology Enhanced Learning, 300-314, 2017 | 18 | 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 International Workshop on Learning Technology for Education in Cloud, 99-109, 2017 | 7 | 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 | 3 | 2017 |