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Martin Hlosta
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2020 – today
- 2024
- [c17]Ivan Moser, Martin Hlosta, Per Bergamin, Umesh Ramnarain, Christo van der Westhuizen, Mafor Penn, Noluthando Mdlalose, Koketso Pila, Ogegbo Ayodele:
Approximating eye gaze with head pose in a virtual reality microteaching scenario for pre-service teachers. LAK Workshops 2024: 272-283 - [e1]Martin Hlosta, Ivan Moser, Brendan Flanagan, Gloria Milena Fernández Nieto, Lixiang Yan, Angela Stewart, Amir Winer, Nitza Geri, Umesh Ramnarain, Christo van der Westhuizen, Atsushi Shimada, Fumiya Okubo, Hsiao-Ting Tseng, Albert C. M. Yang, Owen H. T. Lu, Hiroaki Ogata, Vanessa Echeverría, Roberto Martínez-Maldonado, Yi-Shan Tsai, LuEttaMae Lawrence, Shaveen Singh, Stanislav Pozdniakov, Lujie Karen Chen, Jiaqi Gong, Louise Yarnall, Andy Nguyen, Lele Sha, Jionghao Lin, Mutlu Cukurova, Kshitij Sharma, Linxuan Zhao, Yuheng Li, Yueqiao Jin, Dragan Gasevic, Caitlin Mills, Stephen Hutt:
Joint Proceedings of LAK 2024 Workshops co-located with 14th International Conference on Learning Analytics and Knowledge (LAK 2024), Kyoto, Japan, March 18-22, 2024. CEUR Workshop Proceedings 3667, CEUR-WS.org 2024 [contents] - 2023
- [j7]Christof Imhof
, Ioan-Sorin Comsa
, Martin Hlosta
, Behnam Parsaeifard
, Ivan Moser
, Per Bergamin
:
Prediction of Dilatory Behavior in eLearning: A Comparison of Multiple Machine Learning Models. IEEE Trans. Learn. Technol. 16(5): 648-663 (2023) - [c16]Geoffray Bonnin, Vaclav Bayer
, Miriam Fernández
, Christothea Herodotou
, Martin Hlosta
, Paul Mulholland:
CERSEI: Cognitive Effort Based Recommender System for Enhancing Inclusiveness. EC-TEL 2023: 692-697 - [c15]Christothea Herodotou
, Claire Maguire
, Martin Hlosta
, Paul Mulholland
:
Predictive Learning Analytics and University Teachers: Usage and perceptions three years post implementation. LAK 2023: 68-78 - 2022
- [j6]Martin Hlosta
, Christothea Herodotou, Tina Papathoma
, Anna Gillespie
, Per Bergamin:
Predictive learning analytics in online education: A deeper understanding through explaining algorithmic errors. Comput. Educ. Artif. Intell. 3: 100108 (2022) - [j5]Geoffray Bonnin, Danilo Dessì, Gianni Fenu, Martin Hlosta
, Mirko Marras, Harald Sack:
Guest Editorial of the FGCS Special Issue on Advances in Intelligent Systems for Online Education. Future Gener. Comput. Syst. 127: 331-333 (2022) - [i2]Christof Imhof, Ioan-Sorin Comsa, Martin Hlosta, Behnam Parsaeifard, Ivan Moser, Per Bergamin:
Prediction of Dilatory Behavior in eLearning: A Comparison of Multiple Machine Learning Models. CoRR abs/2206.15079 (2022) - 2021
- [j4]Christothea Herodotou
, Claire Maguire, Nicola McDowell
, Martin Hlosta
, Avinash Boroowa
:
The engagement of university teachers with predictive learning analytics. Comput. Educ. 173: 104285 (2021) - [c14]Vaclav Bayer
, Martin Hlosta
, Miriam Fernández
:
Learning Analytics and Fairness: Do Existing Algorithms Serve Everyone Equally? AIED (2) 2021: 71-75 - [c13]Martin Hlosta
, Christothea Herodotou
, Vaclav Bayer
, Miriam Fernández
:
Impact of Predictive Learning Analytics on Course Awarding Gap of Disadvantaged Students in STEM. AIED (2) 2021: 190-195 - 2020
- [j3]Christothea Herodotou
, Bart Rienties
, Martin Hlosta
, Avinash Boroowa, Chrysoula Mangafa
, Zdenek Zdráhal:
The scalable implementation of predictive learning analytics at a distance learning university: Insights from a longitudinal case study. Internet High. Educ. 45: 100725 (2020) - [c12]Martin Hlosta
, Tina Papathoma, Christothea Herodotou
:
Explaining Errors in Predictions of At-Risk Students in Distance Learning Education. AIED (2) 2020: 119-123 - [c11]Christothea Herodotou, Avinash Boroowa, Martin Hlosta, Bart Rienties:
What Do Distance Learning Students Need From Student Analytics? ICLS 2020
2010 – 2019
- 2019
- [j2]Christothea Herodotou
, Martin Hlosta
, Avinash Boroowa, Bart Rienties
, Zdenek Zdráhal, Chrysoula Mangafa
:
Empowering online teachers through predictive learning analytics. Br. J. Educ. Technol. 50(6): 3064-3079 (2019) - [c10]Dilek Çelik
, Alexander Mikroyannidis
, Martin Hlosta
, Allan Third
, John Domingue
:
ADA: A System for Automating the Learning Data Analytics Processing Life Cycle. EC-TEL 2019: 714-718 - 2018
- [b1]Martin Hlosta:
Klasifikace na nevyvážených datech ; Classification on unbalanced data. Brno University of Technology, Czech Republic, 2018 - [j1]Martin Hlosta
, Zdenek Zdráhal, Jaroslav Zendulka:
Are we meeting a deadline? classification goal achievement in time in the presence of imbalanced data. Knowl. Based Syst. 160: 278-295 (2018) - [c9]Michal Huptych
, Martin Hlosta
, Zdenek Zdráhal, Jakub Kocvara:
Investigating Influence of Demographic Factors on Study Recommenders. AIED (2) 2018: 150-154 - [i1]Martin Hlosta, Drahomira Herrmannova, Lucie Vachova, Jakub Kuzilek, Zdenek Zdráhal, Annika Wolff:
Modelling student online behaviour in a virtual learning environment. CoRR abs/1811.06369 (2018) - 2017
- [c8]Martin Hlosta
, Zdenek Zdráhal, Jaroslav Zendulka:
Ouroboros: early identification of at-risk students without models based on legacy data. LAK 2017: 6-15 - [c7]Christothea Herodotou
, Bart Rienties
, Avinash Boroowa, Zdenek Zdráhal, Martin Hlosta
, Galina Naydenova
:
Implementing predictive learning analytics on a large scale: the teacher's perspective. LAK 2017: 267-271 - [c6]Michal Huptych
, Michal Bohuslavek, Martin Hlosta
, Zdenek Zdráhal:
Measures for recommendations based on past students' activity. LAK 2017: 404-408 - 2016
- [c5]Annika Wolff
, John Moore, Zdenek Zdráhal, Martin Hlosta
, Jakub Kuzilek
:
Data literacy for learning analytics. LAK 2016: 500-501 - 2015
- [d1]Jakub Kuzilek, Martin Hlosta, Zdenek Zdráhal:
Open University Learning Analytics dataset. UCI Machine Learning Repository, 2015 - 2014
- [c4]Philippe Fournier-Viger
, Antonio Gomariz, Michal Sebek, Martin Hlosta:
VGEN: Fast Vertical Mining of Sequential Generator Patterns. DaWaK 2014: 476-488 - [c3]Martin Hlosta, Drahomira Herrmannova, Lucie Vachova, Jakub Kuzilek, Zdenek Zdráhal, Annika Wolff:
Modelling student online behaviour in a virtual learning environment. LAK Workshops 2014 - [c2]Annika Wolff, Zdenek Zdráhal, Drahomira Herrmannova, Jakub Kuzilek, Martin Hlosta:
Developing predictive models for early detection of at-risk students on distance learning modules. LAK Workshops 2014 - 2013
- [c1]Michal Sebek, Martin Hlosta, Jaroslav Zendulka, Tomas Hruska:
MLSP: Mining Hierarchically-Closed Multi-Level Sequential Patterns. ADMA (1) 2013: 157-168
Coauthor Index
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last updated on 2024-08-05 21:23 CEST by the dblp team
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