Seminars@FI: Atsushi Shimada: AI-Powered Learning Analytics for Transforming Education
We are honoured to welcome a special guest at FI MU – Professor Atsushi Shimada from Kyushu University, Japan. His invited talk will cover an intersection of three research areas: learning analytics, machine learning, and multimedia processing. We invite all staff and students to attend this special occasion!
Topic: AI-Powered Learning Analytics for Transforming Education
When: 9 October 2025 at 14:00 h.
Where: KYPO room, Faculty of Informatics MU, Botanická 68a, Brno
Abstract: Learning analytics has become a key approach for understanding and improving learning by analyzing diverse forms of educational data. This invited talk will present how artificial intelligence can be integrated into learning analytics to transform education at multiple levels. We will introduce an approach that combines predictive modelling, personalized feedback, and real-time monitoring with advanced media processing techniques for analyzing multimodal data such as text, video, and handwritten notes. These methods enable detailed insights at the micro level, supporting individual learners through tailored feedback, while also facilitating macro-level initiatives that help learners understand the broader structure and connections across courses and curricula. Drawing on case studies from large-scale lectures and online learning environments, we will illustrate how AI-powered analytics can enhance engagement, improve learning strategies, and support holistic educational experiences. The talk will conclude with future perspectives on trustworthy AI in education and the evolving role of human-AI collaboration in shaping learning environments.
Bio: Atsushi Shimada received his M.E. degree in Information Science and Electrical Engineering from Kyushu University in 2004 and his D.E. degree from the same university in 2007. He is currently a Professor at the Faculty of Information Science and Electrical Engineering, Kyushu University. From 2015 to 2019, he served as a researcher for the JST PRESTO program. His current research interests include learning analytics, pattern recognition, media processing, and image processing. He has received numerous awards, including the MIRU Interactive Presentation Award (2011, 2017), MIRU Demonstration Award (2015), First Place in the Background Models Challenge 2012, the PRMU Research Award (2013), First Place in the SBM-RGBD Challenge (2017), the ITS Symposium Best Poster Award (2018), the JST PRESTO Interest Poster Award (2019), the IPSJ/IEEE Computer Society Young Computer Researcher Award (2019), the CELDA Best Paper Award (2019), and the MEXT Young Scientist Award (2020).
Contact person is RNDr. Valdemar Švábenský, Ph.D., valdemar@mail.muni.cz
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