Open University Learning Analytics Dataset J Kuzilek, M Hlosta, Z Zdrahal Scientific data, 2017 | 508 | 2017 |
A large-scale implementation of predictive learning analytics in higher education: The teachers’ role and perspective C Herodotou, B Rienties, A Boroowa, Z Zdrahal, M Hlosta Educational technology research and development 67, 1273-1306, 2019 | 215 | 2019 |
OU Analyse: analysing at-risk students at The Open University J Kuzilek, M Hlosta, D Herrmannova, Z Zdrahal, J Vaclavek, A Wolff Learning analytics review, 1-16, 2015 | 210 | 2015 |
Ouroboros: early identification of at-risk students without models based on legacy data M Hlosta, Z Zdrahal, J Zendulka Proceedings of the seventh international learning analytics & knowledge …, 2017 | 160 | 2017 |
The scalable implementation of predictive learning analytics at a distance learning university: Insights from a longitudinal case study C Herodotou, B Rienties, M Hlosta, A Boroowa, C Mangafa, Z Zdrahal The Internet and Higher Education 45, 100725, 2020 | 140 | 2020 |
Empowering online teachers through predictive learning analytics C Herodotou, M Hlosta, A Boroowa, B Rienties, Z Zdrahal, C Mangafa British Journal of Educational Technology 50 (6), 3064-3079, 2019 | 120 | 2019 |
Developing predictive models for early detection of at-risk students on distance learning modules A Wolff, Z Zdrahal, D Herrmannova, J Kuzilek, M Hlosta | 109 | 2014 |
Implementing predictive learning analytics on a large scale: the teacher's perspective C Herodotou, B Rienties, A Boroowa, Z Zdrahal, M Hlosta, G Naydenova Proceedings of the seventh international learning analytics & knowledge …, 2017 | 79 | 2017 |
Exploring critical factors of the perceived usefulness of a learning analytics dashboard for distance university students I Rets, C Herodotou, V Bayer, M Hlosta, B Rienties International Journal of Educational Technology in Higher Education 18, 1-23, 2021 | 60 | 2021 |
VGEN: Fast Vertical Mining of Sequential Generator Patterns P Fournier-Viger, A Gomariz, M Šebek, M Hlosta Data Warehousing and Knowledge Discovery: 16th International Conference …, 2014 | 56 | 2014 |
The engagement of university teachers with predictive learning analytics C Herodotou, C Maguire, N McDowell, M Hlosta, A Boroowa Computers & Education 173, 104285, 2021 | 40 | 2021 |
Data literacy for learning analytics A Wolff, J Moore, Z Zdrahal, M Hlosta, J Kuzilek Proceedings of the sixth international conference on learning analytics …, 2016 | 37 | 2016 |
Modelling student online behaviour in a virtual learning environment M Hlosta, D Herrmannova, L Vachova, J Kuzilek, Z Zdrahal, A Wolff arXiv preprint arXiv:1811.06369, 2018 | 34 | 2018 |
Learning Analytics and Fairness: Do Existing Algorithms Serve Everyone Equally? V Bayer, M Hlosta, M Fernandez International Conference on Artificial Intelligence in Education, 2021 | 26 | 2021 |
Impact of Predictive Learning Analytics on Course Awarding Gap of Disadvantaged students in STEM M Hlosta, C Herodotou, M Fernandez International Conference on Artificial Intelligence in Education, 2021 | 19 | 2021 |
Predictive learning analytics in online education: A deeper understanding through explaining algorithmic errors M Hlosta, C Herodotou, T Papathoma, A Gillespie, P Bergamin Computers and Education: Artificial Intelligence 3, 100108, 2022 | 15 | 2022 |
Are we meeting a deadline? classification goal achievement in time in the presence of imbalanced data M Hlosta, Z Zdrahal, J Zendulka Knowledge-Based Systems 160, 278-295, 2018 | 14 | 2018 |
Constrained classification of large imbalanced data by logistic regression and genetic algorithm M Hlosta, R Stríz, J Kupcík, J Zendulka, T Hruska International Journal of Machine Learning and Computing 3 (2), 214, 2013 | 14 | 2013 |
Exploring pre-service teachers’ intentions of adopting and using virtual reality classrooms in science education AA Ogegbo, M Penn, U Ramnarain, O Pila, C Van Der Westhuizen, ... Education and Information Technologies 29 (15), 20299-20316, 2024 | 13 | 2024 |
Prediction of dilatory behavior in elearning: A comparison of multiple machine learning models C Imhof, IS Comsa, M Hlosta, B Parsaeifard, I Moser, P Bergamin IEEE Transactions on Learning Technologies 16 (5), 648-663, 2022 | 12 | 2022 |