Vaclav Bayer

Full-Stack Web Developer


Publications

Hlosta, Martin, Herodotou, Christothea , Fernandez, Miriam and Bayer, Vaclav(2021). Impact of Predictive Learning Analytics on Course Awarding Gap of Disadvantaged students in STEM. In: 22nd International Conference on Artificial Intelligence in Education, AIED 2021, Lecture Notes in Artificial Intelligence, Springer.

Bayer, Vaclav, Hlosta, Martin and Fernandez, Miriam(2021). Learning Analytics and Fairness: Do Existing Algorithms Serve Everyone Equally? In: AIED 2021; 22nd International Conference on Artificial Intelligence in Education, 14-18 Jun 2021, ONLINE from Utrecht.

Hlosta, Martin, Bayer, Vaclav and Zdrahal, Zdenek(2020). Mini Survival Kit: Prediction based recommender to help students escape their critical situation in online courses. In: Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK20), 23-27 Mar 2020, Frankfurt am Main, Germany.

Hlosta, Martin, Zdrahal, Zdenek, Bayer, Vaclav and Herodotou, Christothea (2020). Why Predictions of At-Risk Students Are Not 100% Accurate? Showing Patterns in False Positive and False Negative Predictions. In: Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK20), 23-27 Mar 2020, Frankfurt am Main, Germany.

Pontika, Nancy, Knoth, Petr, Anastasiou, Lucas , Charalampous, Aristotelis , Cancellieri, Matteo, Pearce, Samuel and Bayer, Vaclav(2017). The uptake of the CORE recommender in repositories. OpenRepositories2017.

Knoth, Petr, Anastasiou, Lucas , Charalampous, Aristotelis , Cancellieri, Matteo, Pearce, Samuel, Pontika, Nancy and Bayer, Vaclav(2017). Towards effective research recommender systems for repositories. In: Open Repositories 2017, 26-30 Jun 2017, Brisbane, Australia.