Currently browsing: Items authored or edited by Vaclav Bayer https://orcid.org/0000-0001-8953-6335

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Generated on Sat Jan 28 20:38:31 2023 GMT.

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Bayer, Vaclav; Hlosta, Martin and Fernandez, Miriam (2021). Learning Analytics and Fairness: Do Existing Algorithms Serve Everyone Equally? In: Artificial Intelligence in Education. AIED 2021. Lecture Notes in Computer Science, vol 12749 (Roll, I.; McNamara, D.; Sosnovsky, S.; Luckin, R. and Dimitrova, V. eds.), Springer.

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: Artificial Intelligence in Education: 22nd International Conference, AIED 2021, Utrecht, the Netherlands, June 14-18, 2021, Proceedings, Part II (Roll, Ido; McNamara, Danielle; Sosnovsky, Sergey; Luckin, Rose and Dimitrova, Vania eds.), Lecture Notes in Artificial Intelligence, Springer, Cham, pp. 190–195.

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.

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.

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