Herodotou, C; Carr, J; Shrestha, S; Comfort, C: Bayer, V; Maguire, C: Lee, J; Andrews, H; Mulholland, P; and Fernandez, M. (2025) Journal of Learning Analytics <\/a><\/strong>A participatory approach to designing a student-facing dashboard for online and distance education<\/p>\n\n\n\n Herodotou, C; Carr, J; Shrestha, S; Comfort, C: Bayer, V; Maguire, C: Lee, J; Mulholland, P; and Fernandez, M. (2025) Prescriptive analytics motivating distance learning student action: A case study of a student-facing dashboard. <\/a><\/strong>In: LAK25: The 15th International Learning Analytics and Knowledge Conference (LAK 2025), ACM, New York, NY, USA, (In press).<\/p>\n\n\n\n Bayer, V; Mulholland, P; Hlosta, M; Farrell, T; Herodotou, C; & Fernandez, M. (2024). Co-creating an equality diversity and inclusion learning analytics dashboard for addressing awarding gaps in higher education. <\/a><\/strong>in British Journal of Educational Technology.<\/p>\n\n\n\n Herodotou, Christothea; Maguire, Claire; Hlosta, Martin and Mulholland, Paul (2023). Predictive Learning Analytics and University Teachers: Usage and perceptions three years post implementation <\/a><\/strong>In: LAK2023: LAK23: 13th International Learning Analytics and Knowledge Conference, pp. 68-78.<\/p>\n\n\n\n Rets, Irina; Herodotou, Christothea and Gillespie, Anna (2023). Six Practical Recommendations Enabling Ethical Use of Predictive Learning Analytics in Distance Education <\/a><\/strong>Journal of Learning Analytics (Early Access)<\/p>\n\n\n\n Hlosta M., Mutwarasibo, F., Farrell T., Bayer V. and Fernandez M. (2022). Understanding the BAME awarding gap at The Open University by means of quantitative and qualitative data analytics<\/a><\/strong>. 2020-22 eSTEem Project Final Report.<\/p>\n\n\n\n Boroowa, A. and Herodotou, C. (2022). Learning Analytics in Open and Distance Higher Education: The Case of the Open University UK <\/a><\/strong>. In: Prinsloo, P.; Slade, S. and Khalil, M. eds. Learning Analytics in Open and Distributed Learning.SpringerBriefs in Education. Singapore: Springer, pp. 46-62.<\/p>\n\n\n\n Rienties, Bart and Herodotou, Christothea (2022). Making sense of learning data at scale. In: Sharpe, Rhona; Bennett, Sue and Varga-Atkins, Tu\u00cc\u02c6nde eds. Handbook for Digital Higher Education <\/a><\/strong>. Cheltenham: Edward Elgar Publishing, pp. 260-270.<\/p>\n\n\n\n Hlosta, Martin; Herodotou, Christothea; Papathoma, Tina; Gillespie, Anna and Bergamin, Per (2022). Predictive learning analytics in online education: A deeper understanding through explaining algorithmic errors <\/a><\/strong>. Computers and Education: Artificial Intelligence, 3, article no. 100108.<\/p>\n\n\n\n Herodotou C., Maguire C., McDowell N., Hlosta M., Boroowa A. The engagement of university teachers with predictive learning analytics <\/a><\/strong>Computers & Education, Volume 173, November 2021, 104285<\/p>\n\n\n\n Rets I., Herodotou C., Bayer V., Hlosta M., and Rienties B. Exploring critical factors of the perceived usefulness of a learning analytics dashboard for distance university students <\/a><\/strong>International Journal of Educational Technology in Higher Education (In Press).<\/p>\n\n\n\n Bayer V., Hlosta M., Fernandez M. Learning Analytics and Fairness: Do Existing Algorithms Serve Everyone Equally? <\/a><\/strong>AIED 2021; 22nd International Conference on Artificial Intelligence in Education, 14-18 Jun 2021, ONLINE from Utrecht.<\/p>\n\n\n\n Hlosta M., Herodotou Ch., Fernandez M., Bayer V. Impact of Predictive Learning Analytics on Course Awarding Gap of Disadvantaged students in STEM <\/a><\/strong>AIED 2021; 22nd International Conference on Artificial Intelligence in Education, 14-18 Jun 2021, ONLINE from Utrecht.<\/p>\n\n\n\n Herodotou Ch. Predictive learning analytics: An empowering tool in the hands of online teachers – Society for Learning Analytics Research (SoLAR) (2021) <\/a><\/strong>SoLAR Nexus series, 29th Apr 2021<\/p>\n\n\n\n Kaliisa, Rogers; Gillespie, Anna; Herodotou, Christothea; Kluge, Anders and Rienties, Bart (2021). Teachers’ Perspectives on the Promises, Needs and Challenges of Learning Analytics Dashboards: Insights from Institutions Offering Blended and Distance Learning <\/a><\/strong>. In: Sahin, Muhittin and Dirk, Ifenthaler eds. Visualizations and Dashboards for Learning Analytics.Advances in Analytics for Learning and Teaching. Cham: Springer, pp. 351-370.<\/p>\n\n\n\n Hlosta M., Papathoma T., Herodotou C. Explaining errors in predictions of at-risk students in distance learning education <\/a><\/strong>International Conference on Artificial Intelligence in Education (AIED’20), 06-10 Jul 2020, Ifrane, Morocco<\/p>\n\n\n\n Hlosta M., Bayer V., Zdrahal Z. Mini Survival Kit: Prediction based recommender to help students escape their critical situation in online courses <\/a><\/strong>Edrecsys@LAK Worskhop at 10th International Conference on Learning Analytics and Knowledge (LAK’20)<\/p>\n\n\n\n Herodotou C., Boroowa A., Hlosta M., Rienties B. What do distance learning students seek from student analytics? <\/a><\/strong>International Conference on Learning Sciences (ICLS’20), 19-23 Jun 2020, Nashville, TN, USA<\/p>\n\n\n\n Hlosta M., Zdrahal Z., Bayer V., Herodotou C. Why Predictions of At-Risk Students Are Not 100% Accurate? Showing Patterns in False Positive and False Negative Predictions <\/a><\/strong>10th International Conference on Learning Analytics and Knowledge (LAK20)<\/p>\n\n\n\n Herodotou C., Rienties B., Hlosta M., Boroowa A., Mangafa C., Zdrahal Z. The scalable implementation of predictive learning analytics at a distance learning university: Insights from a longitudinal case study <\/a>The Internet and Higher Education, Volume 45, April 2020, 100725<\/p>\n\n\n\n Herodotou, Christothea; Rienties, Bart; Verdin, Barry and Boroowa, Avinash (2019). Predictive learning analytics ‘at scale’: Guidelines to successful implementation in Higher Education based on the case of the Open University UK <\/a><\/strong>. Journal of Learning Analytics, 6(1) pp. 85-95.<\/p>\n\n\n\n Hlosta M., Kocvara J., Beran D., Zdrahal Z. Visualisation of key splitting milestones to support interventions <\/a><\/strong>LAK ’19: Companion Proceedings 9th International Conference on Learning Analytics & Knowledge<\/p>\n\n\n\n Herodotou C., Rienties B., Boroowa A., Zdrahal Z., Hlosta M. A large-scale implementation of Predictive Learning Analytics in Higher Education: The teachers’ role and perspective <\/a><\/strong>Educational Technology Research and Development<\/p>\n\n\n\n Herodotou C., Hlosta M., Boroowa A., Rienties B., Zdrahal Z., Mangafa C. Empowering online teachers through predictive learning analytics <\/a><\/strong>British Journal of Educational Technology pp. 1-17.<\/p>\n\n\n\n Hlosta M., Zdrahal Z., Zendulka J. Are we meeting a deadline? classification goal achievement in time in the presence of imbalanced data <\/a><\/strong>Knowledge-Based Systems. ISSN 09507051<\/p>\n\n\n\n Huptych M., Hlosta M., Zdrahal Z., Kocvara J. Investigating Influence of Demographic Factors on Study Recommenders <\/a><\/strong>Artificial Intelligence in Education. AIED 2018. Lecture Notes in Computer Science, volume 10948. Springer, Cham<\/p>\n\n\n\n Nguyen, Q., Huptych, M. and Rienties, B. Linking students’ timing of engagement to learning design and academic performance <\/a><\/strong>LAK ’18: Proceedings of the Seventh International Learning Analytics & Knowledge Conference<\/p>\n\n\n\n Kuzilek J., Hlosta M., Zdrahal Z. Open University Learning Analytics dataset <\/a><\/strong>Nature Scientific Data 4:170171 doi: 10.1038\/sdata.2017.171<\/a><\/strong> (2017).<\/p>\n\n\n\n Rienties B., Clow D., Coughlan T., Cross S., Edwards C., Gaved M., Herodotou C., Hlosta M., Jones J., Rogaten J., Ullmann T. Scholarly insight Autumn 2017: a Data wrangler perspective <\/a><\/strong>The Open University<\/p>\n\n\n\n Herodotou C., Gilmour A., Boroowa A., Rienties B., Zdrahal Z., Hlosta M. Predictive modelling for addressing students’ attrition in Higher Education: The case of OU Analyse <\/a><\/strong>CALRG Annual Conference 2017<\/p>\n\n\n\n Herodotou C., Rienties B., Boroowa A., Zdrahal Z., Hlosta M., Naydenova G. Implementing predictive learning analytics on a large scale: the teacher’s perspective <\/a><\/strong>LAK ’17: Proceedings of the Seventh International Learning Analytics & Knowledge Conference<\/p>\n\n\n\n Huptych M., Bohuslavek M., Hlosta M., Zdrahal Z., Measures for recommendations based on past students’ activity <\/a><\/strong>LAK ’17: Proceedings of the Seventh International Learning Analytics & Knowledge Conference<\/p>\n\n\n\n Hlosta M., Zdrahal Z., Zendulka J. Ouroboros: early identification of at-risk students without models based on legacy data <\/a><\/strong>LAK ’17: Proceedings of the Seventh International Learning Analytics & Knowledge Conference<\/p>\n\n\n\n Rienties B., Cross S., Zdrahal, Z. Implementing a Learning Analytics Intervention and Evaluation Framework: what works? <\/a><\/strong>Big Data and Learning Analytics in Higher Education: Current Theory and Practice<\/p>\n\n\n\n Kuzilek, J., Hlosta, M., Herrmannova, D., Zdrahal, Z. and Wolff, A. OU Analyse: Analysing At-Risk Students at The Open University. <\/a><\/strong>Learning Analytics Review, no. LAK15-1, March 2015, ISSN: 2057-7494.<\/p>\n\n\n\n Herrmannova, D., Hlosta, M., Kuzilek, J., Zdrahal, Z. Evaluating weekly predictions of at-risk students at the Open University: results and issues. EDEN 2015<\/a><\/strong>, Barcelona, Spain.<\/p>\n\n\n\n Wolff, A., Zdrahal, Z., Herrmannova, D., Kuzilek, J. and Hlosta, M. Developing predictive models for early detection of at-risk students on distance learning modules <\/a><\/strong>, Workshop: Machine Learning and Learning Analytics at LAK, Indianapolis<\/p>\n\n\n\n Hlosta, M., Herrmannova, D., Vachova, L., Kuzilek, J., Zdrahal, Z. and Wolff, A. Modelling student online behaviour in a virtual learning environment <\/a><\/strong>, Workshop: Machine Learning and Learning Analytics at LAK, Indianapolis<\/p>\n\n\n\n Wolff, A., Zdrahal, Z., Nikolov, A. and Pantucek, M., Improving retention: predicting at-risk students by analysing clicking behaviour in a virtual learning environment<\/a><\/strong>, Learning Analytics and Knowledge<\/p>\n\n\n\n Wolff, A., Zdrahal, Z., Herrmannova, D. and Knoth, P., Predicting Student Performance from Combined Data Sources<\/a><\/strong>, in eds. Alejandro Pe\u00c3\u00b1a-Ayala, Educational Data Mining: Applications and Trends, 524, Springer<\/p>\n\n\n\n2024<\/h3>\n\n\n\n
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