Martin Hlosta

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 22

Top Topics

Machine Learning Models

Learning Analytics

Distance Learning

Top Venues

Publications

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)
Christothea Herodotou, Claire Maguire, Martin Hlosta, Paul Mulholland
Predictive Learning Analytics and University Teachers: Usage and perceptions three years post implementation. LAK (2023)
Geoffray Bonnin, Vaclav Bayer, Miriam Fernández, Christothea Herodotou, Martin Hlosta, Paul Mulholland
CERSEI: Cognitive Effort Based Recommender System for Enhancing Inclusiveness. EC-TEL (2023)
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) (2023)
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 (2022)
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 (2022)
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 (2022)
Vaclav Bayer, Martin Hlosta, Miriam Fernández
Learning Analytics and Fairness: Do Existing Algorithms Serve Everyone Equally? AIED (2) (2021)
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)
Christothea Herodotou, Claire Maguire, Nicola McDowell, Martin Hlosta, Avinash Boroowa
The engagement of university teachers with predictive learning analytics. Comput. Educ. 173 (2021)
Martin Hlosta, Tina Papathoma, Christothea Herodotou
Explaining Errors in Predictions of At-Risk Students in Distance Learning Education. AIED (2) (2020)
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 (2020)
Christothea Herodotou, Avinash Boroowa, Martin Hlosta, Bart Rienties
What Do Distance Learning Students Need From Student Analytics? ICLS (2020)
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)
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) (2019)
Michal Huptych, Martin Hlosta, Zdenek Zdráhal, Jakub Kocvara
Investigating Influence of Demographic Factors on Study Recommenders. AIED (2) (2018)
Martin Hlosta, Drahomira Herrmannova, Lucie Vachova, Jakub Kuzilek, Zdenek Zdráhal, Annika Wolff
Modelling student online behaviour in a virtual learning environment. CoRR (2018)
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 (2018)
Michal Huptych, Michal Bohuslavek, Martin Hlosta, Zdenek Zdráhal
Measures for recommendations based on past students' activity. LAK (2017)
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)
Martin Hlosta, Zdenek Zdráhal, Jaroslav Zendulka
Ouroboros: early identification of at-risk students without models based on legacy data. LAK (2017)
Annika Wolff, John Moore, Zdenek Zdráhal, Martin Hlosta, Jakub Kuzilek
Data literacy for learning analytics. LAK (2016)
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)
Martin Hlosta, Drahomira Herrmannova, Lucie Vachova, Jakub Kuzilek, Zdenek Zdráhal, Annika Wolff
Modelling student online behaviour in a virtual learning environment. LAK Workshops (2014)
Philippe Fournier-Viger, Antonio Gomariz, Michal Sebek, Martin Hlosta
VGEN: Fast Vertical Mining of Sequential Generator Patterns. DaWaK (2014)
Michal Sebek, Martin Hlosta, Jaroslav Zendulka, Tomas Hruska
MLSP: Mining Hierarchically-Closed Multi-Level Sequential Patterns. ADMA (1) (2013)