Showing all 14 Publications linked to Martin Hlosta

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Research Associate
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In KMi, I work as a Research Associate acting as a technical lead and a data scientist of OU Analyse Project (https://analyse.kmi.open.ac.uk). The project is focused on improving student retention at Open University using machine learning techniques. I am exploring how to best use OUAnalyse to teachers (Associate Lecturers) in order to better use data and analytics for improving student outcomes. Moreover, I am responsible fore design and the development of the Curriculum Analytics Tool...

Keys: OU Analyse Project, machine learning, CAT(Curriculum Analytics Tool)


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Hlosta, M. and Zendulka, Z. (2018) Are we meeting a deadline? classification goal achievement in time in the presence of imbalanced data, Knowledge Based Systems, Elsevier

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Huptych, M., Hlosta, M., Zdrahal, Z. and Kocvara, J. (2018) Investigating Influence of Demographic Factors on Study Recommenders, Poster at Artificial Intelligence in Education, Springer, Cham

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Kuzilek, J., Hlosta, M. and Zdrahal, Z. (2017) Open University Learning Analytics dataset, Scientific Data, 4, Nature Publishing Group

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Herodotou, C., Gilmour, A., Boroowa, A., Rientes, B., Zdrahal, Z. and Hlosta, M. (2017) Predictive modelling for addressing students' attrition in Higher Education: The case of OU Analyse, CALRG Annual Conference 2017, The Open University

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Hlosta, M., Zdrahal, Z. and Zendulka, J. (2017) Ouroboros: Early identification of at-risk students without models based on legacy data, Learning Analytics & Knowledge (LAK 17), ACM

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Herodotou, C., Rienties, B., Boroowa, A., Zdrahal, Z., Hlosta, M. and Naydenova, G. (2017) Implementing predictive learning analytics on a large scale: the teacher's perspective, Learning Analytics & Knowledge Conference (LAK'17), ACM

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Huptych, M., Bohuslavek, M., Hlosta, M. and Zdrahal, Z. (2017) Measures for recommendations based on past students' activity, Learning Analytics & Knowledge (LAK 17), ACM

 

Kuzilek, J., Hlosta, M. and Zdrahal, Z. (2016) Open University Learning Analytics Dataset, Workshop: Data Literacy for Learning Analytics at Learning Analytics and Knowledge (LAK 16)

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Zdrahal, Z., Hlosta, M. and Kuzilek, J. (2016) Analysing performance of first year engineering students, Workshop: Data Literacy for Learning Analytics at Learning Analytics and Knowledge (LAK 16)

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Herrmannova, D., Hlosta, M., Kuzilek, J. and Zdrahal, Z. (2015) Evaluating Weekly Predictions of At-Risk Students at The Open University: Results and Issues, EDEN 2015, Barcelona, Spain

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Kuzilek, J., Hlosta, M., Herrmannova, D., Vaclavek, J., Zdrahal, Z. and Wolff, A. (2015) OU Analyse: Analysing At-Risk Students at The Open University, Learning Analytics and Knowledge (LAK15), Learning Analytics Review, LAK15-1, LACE project

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Wolff, A., Zdrahal, Z., Herrmannova, D., Kuzilek, J. and Hlosta, M. (2014) Developing predictive models for early detection of at-risk students on distance learning modules, Workshop: Machine Learning and Learning Analytics at Learning Analytics and Knowledge (LAK), Indianapolis

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Hlosta, M., Herrmannova, D., Vachova, L., Kuzilek, J., Zdrahal, Z. and Wolff, A. (2014) Modelling student online behaviour in a virtual learning environment, Workshop: Machine Learning and Learning Analytics at Learning Analytics and Knowledge (LAK), Indianapolis

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Hlosta, M., Zdrahal, Z. and Zendulka, J.Are we meeting a deadline? classification goal achievement in time in the presence of imbalanced data, Knowledge-Based Systems, 160, pp. 278-295, Elsevier

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