Prof. Songhua Du

Guangdong University of Technology, China

Du, Helen S. graduated from City University of Hong Kong in 2008 with a Ph.D. in Information Systems. 

Professor of the Department of Data Science and Business Intelligence, School of Management, and Doctoral Supervisor. Also serves as the Director of the International Cooperation and Accreditation Center of the School of Management. Special Appointed Professor of the "Hundred Talents Program" of Guangdong University of Technology (2014-2018). With extensive teaching and research experience in the fields of e-commerce and information management. Currently, the main research topics include behavioral analysis empowered by digital intelligence, human-computer and human-intelligence interaction, gamification design, pro-environmental behavior, and green innovation and entrepreneurship models. Relevant research achievements have been selected as typical case study results by the Ministry of Education in 2023 and have been highly cited in ESI. Has led 3 national research projects, 3 provincial research projects, and 1 project of the Guangdong Province Graduate Education Innovation Program, etc. Has published over 40 academic papers in authoritative domestic and international journals such as International Journal of Information Management, Decision Support Systems, Journal of Cleaner Production, Internet Research, Journal of the Association for Information Science and Technology, International Journal of Human-Computer Studies, Nankai Business Review, and Operations Research and Management. Currently serves as a member of the editorial board of the SSCI journal Online Information Review, associate editor of the EI journal Journal of Information & Knowledge Management, and holds social positions such as a member of the Economic Committee of the Guangdong Provincial Committee of the China Democratic League and a member of the Teaching Steering Committee for E-commerce Majors in Undergraduate Colleges of Guangdong Province. 

In addition, I have many years of international practical experience in enterprise information management. I have worked as an information system analyst for several years at Ontario Power Generation in Ontario, Canada and PCCW in Hong Kong.

Assoc. Prof. Chen Xieling

Guangzhou University, China

Dr. Chen Xieling graduated with a Ph.D. from The Education University of Hong Kong in 2022. In 2023, she joined the School of Education at Guangzhou University as an Outstanding Young Scholar of the "Hundred Talents Program". She is currently an Associate Professor and Master's supervisor at Guangzhou University. Dr. Chen has led several research projects, including those funded by the National Natural Science Foundation of China and the Guangdong Provincial Social Science Planning Program. Her research interests include AI in education, technology-enhanced learning, and natural language processing. To date, Dr. Chen has published over 80 papers in national and international journals and conferences, with more than 40 of these appearing in prominent SCI/SSCI journals such as Computers & Education, Information Processing & Management, and the International Journal of Educational Technology in Higher Education. Two of her papers have been recognized as ESI Highly Cited Papers. She serves as Executive Editor or Executive Associate Editor for Elsevier journals including Computers and Education: Artificial Intelligence, Computers and Education: X Reality, and the Natural Language Processing Journal. She holds two software copyrights and has applied for three invention patents. Dr. Chen has received awards for her research, including the Best Paper Award at the 2020 International Conference on Blended Learning. She has also served as General Chair or Vice Chair for conferences such as the BESC 2022 Special Session and GCCCE 2023 C6. As of November 2024, her work has been cited 4,800 times on Google Scholar, with an h-index of 31 and an i10-index of 45. Stanford University has listed her as one of the World's Top 2% Scientists in three consecutive years (2022, 2023, and 2024).

Speech Title: AI and Big Data-driven Online Learning Analytics

Abstract: In recent years, empirical MOOC research has increasingly emphasized educational data mining and learner-centered perspectives such as learner perceptions and satisfaction. This keynote synthesizes research on online course review analysis, beginning with a systematic review of the theories, themes, and methods used in this field. Building on this foundation, I will highlight several AI- and big data-driven studies, including the use of deep learning, sentiment analysis, and structural topic modeling to extract insights from learner reviews. Key contributions include analyses using fine-tuned BERT models, multilingual sentiment classification, and novel review mining approaches to understand and predict MOOC satisfaction. Further, I will explore recent advances in automated classification of online learner-generated content, such as Chinese programming MOOC reviews and online course evaluations, using GPT-augmented data, deep neural networks, and domain-specific transformer models. Lastly, I will discuss broader applications of AI in online learning analytics, including methods like text mining with analytic hierarchy processes and epistemic/social network analysis to evaluate teaching and learning interactions. This talk aims to provide a comprehensive overview of how AI and big data are transforming our understanding of online learning at scale, with implications for both research and practice.

Assoc. Prof. Madihah Sheikh Abdul Aziz

International Islamic University Malaysia, Malaysia

Dr. Madihah is a senior lecturer and researcher specializing in User Experience (UX) and User Interface (UI) Design, Information Visualization, and Creative Media Design. She holds a Bachelor's Degree in Information Technology from Universiti Kebangsaan Malaysia, a Master's in Computer Science from Universiti Putra Malaysia, and a PhD from Swinburne University of Technology, Melbourne, Australia, where she received a Research Fellowship Grant. With extensive experience in teaching and research, Dr. Madihah has contributed to the fields of UI/UX, human-computer interaction, storytelling in visualization, and digital media design. She has also served as an expert panel member for academic evaluations and has published widely in indexed journals and conferences, reflecting her dedication to advancing knowledge and practice in her areas of expertise.