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Keynote Speech 1
Chair: Carol Hui-Chun Chu
Professor Gwo-Jen Hwang (National Taichung University of Education, Taiwan)
Learning analytics for providing personalized support in blended learning settings
Abstract:
The advancement of computing and communication technologies has significantly changed the conception of teaching and learning in the past decades. Blended learning has become an important educational mode nowadays. In this talk, Prof. Hwang is going to address the challenges of conventional blended learning; moreover, a modified blended learning mode with support from learning analytics is introduced to cope with the problems. Prof. Hwang is going to present how to effectively use learning analytics for providing learning support in different stages of blended learning, such as using data collected from students’ learning process to decide what interventions to give to individual students to maximize their learning performance as well as how the intervention can be evaluated and improved. In addition, Prof. Hwang is going to present the strategies and tools for collecting and analyzing students’ learning data, such as their answers to the test items, interactive content in discussion forums and online learning logs, to provide personalized guidance or supports as well as to identify the problems individual students have encountered. Several real cases will be given to demonstrate how learning analytics can be applied in class.
Bio:
Chair Professor and Vice President of National Taichung University of Education, Taiwan
Prof. Gwo-Jen Hwang is a Chair Professor and Vice President of National Taichung National University of Education as well as the Chair Professor of National Taiwan University of Science and Technology, Taiwan. Professor Hwang's academic specialties include mobile and ubiquitous learning, game-based learning, flipped learning, and artificial intelligence applications in education. He has led more than 150 projects and received numerous research awards, including the "Annual Most Outstanding Researcher Award" from the National Science and Technology Council in 2007, 2010, and 2013, the "Outstanding ICT Elite Award" in 2015, and the "Ministry of Education's Excellent Teacher Award" in 2019. In 2022, he was honored as an Appointed Outstanding Research Award by the National Science and Technology Council, Taiwan.
Prof. Hwang has published more than 800 papers, including around 450 in SSCI journals. He has served as a reviewer/editor/guest editor/editor-in-chief for more than 50 SSCI/SCI academic journals. He currently serves as a reviewer/editor/guest editor/editor-in-chief of Computers & Education: Artificial Intelligence (Scopus, Q1; EI), International Journal of Mobile Learning and Organisation (Scopus, Q1; ESCI), and Journal of Computers in Education (Scopus, Q1; ESCI); he also serves as Associate Editor of IEEE Transactions on Education (SCI).
Keynote Speech 2
Chair: Leon Chi-Un Lei
Associate Professor Tsubasa Minematsu (Kyushu Institute of Technology, Japan)
A Study on Teacher and Learner Agents in Learning and Teaching Support Using Generative AI
Abstract:
Generative AI, including recent large-scale language models (LLMs), is expected to lower the barriers to AI adoption in educational and learning environments due to its high accuracy and versatility. For simple question generation and question answering, tools such as ChatGPT can already be utilized effectively. In this talk, Minematsu will introduce methods to improve educational and learning environments by allowing large-scale language models to partially assume the roles of teachers and learners. From the teacher's perspective, he will present methods for having LLMs execute basic tasks such as question generation and lecture explanations. From the learner's perspective, Minematsu will discuss approaches to leverage LLMs as virtual learners and strategies for tuning LLMs for effective educational use.
Bio:
Associate Professor in the Division of Next-Generation Open Education Promotion, Data-Driven Innovation Initiative, Kyushu University, Japan
Tsubasa Minematsu is an Associate Professor in the Division of Next-Generation Open Education Promotion, Data-Driven Innovation Initiative, Kyushu University. He received his Ph.D. in Engineering from Kyushu University, Fukuoka, Japan, in 2018. His research interests include learning analytics, image processing, and pattern recognition. Recently, he has developed learning support systems such as dashboard systems and technologies for educational data analysis using machine learning and large language models. In addition, He has received several awards, including the SBM-RGBD Challenge First Place (2017) and the CELDA Best Paper Award (2019).
Prof. Tsubasa Minematsu has published research papers in international conferences and journals such as Educational Data Mining, Artificial Intelligence in Education, and Pattern Recognition Letters. He has served as a reviewer for SSCI academic journals and CORE ranking A conferences.
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