Mutlu Cukurova is Professor of Learning and Artificial Intelligence at University College London. Professor Cukurova investigates the potential of AI to understand and support human learning with a particular interest in “learning how to learn” and solving complex problems collaboratively. His work emphasises human-AI complementarity, aiming to address the pressing socio-educational challenge of preparing people for a future with AI systems that will require a great deal more than the routine cognitive skills currently prized by many education systems and traditional approaches to automation. Professor Cukurova is the Director of the UCLAIT team and works with UNESCO's Unit for Technology and AI in Education as an external expert. He contributed to numerous influential policymaking documents including UNESCO's recent report on Guidance for generative AI in education and research. He is currently leading the report on UNESCO AI competency frameworks for teachers and students. He was the programme chair of the International Conference of AI in Education in 2020, currently serving as the editor of the British Journal of Educational Technology and an Associate Editor of the International Journal of Child-Computer Interaction.
AI in Education is more than tools like ChatGPT. This talk presents a multi-dimensional view of AI's role in learning and education, emphasizing the intricate interplay between AI and the cognitive processes of learning. Professor Cukurova challenges the prevalent narrow conceptualization of AI as stochastic tools, highlighting the cognitive diversity inherent in AI algorithms, and posits that AI can serve as an instrument for understanding human learning. Early learning sciences and AI in Education research, which saw AI as an analogy for human intelligence, have diverged from this perspective, prompting a need to rekindle this connection. The presentation delves into three conceptualizations of AI in education: the externalization of cognition, the internalization of AI models to influence human thought processes, and the extension of human cognition via tightly integrated human-AI systems. Professor Cukurova argues for a balanced view that recognizes AI's limitations and the need for AI systems that support human agency, facilitate the internalization of learning process models, and enhance human cognition without replacing it. The presentation concludes with an advocacy for a broader educational approach that includes educating about AI itself and innovating educational systems to remain relevant in a world with ubiquitous AI.
Professor Wu Feng works at the Graduate School of Education, Peking University. He is the director of Business-Education Research Center of Peking University and the chairman of the Human Resources Education Professional Committee of the China Adult Education Association. His research areas include digital learning, human resource development, and geriatric education. He has presided over 40 projects including major projects of the National Social Science Foundation and projects of the Ministry of Education. He has published one hundred articles in Educational Research, Journal of Peking University and so on. He has won the prize of Peking University's Research Outstanding Achievement Award, the prize of the National Educational Science Research Award, the Prize of Beijing Higher Education Teaching Achievements, the Prize of Talent-Teacher Award in Peking University.
China is transitioning from a stage of rapid economic growth to a stage of high-quality economic development. Internet is a characteristic of China's times. How to fully utilize and release the dividends of the Internet to promote the development of China’s human resources is of significance. The emergence of the Internet has reconstructed a new view of learning time and space, bringing double dividends to the development of human resources. Since 1999, the Internet has brought three new models to China's human resources development, namely the National Distance Education Plan of the Academic Qualification Model, the Enterprise Digital Learning Project of the Ability Model, and the Knowledge Model of university globalization MOOC movement, they have rapidly promoted the development of China's human resources. These three models are facing bottlenecks for further development, and there is still room for greater dividends. The article puts forward corresponding educational policy suggestions, which are: implement the national digital learning project for small and medium-sized enterprises, carry out distance postgraduate education, establish a credit certification system, and promote lifelong learning legislation. These will greatly unleash the dividends of the Internet and promote the rapid development of China’s human resources.
Professor Maiga Chang is a Full Professor in the School of Computing and Information Systems at Athabasca University, Canada. He is IEEE Senior Member. Professor Chang has been appointed as an IEEE Computer Society Distinguished Visitor for 2023 to 2025 and received Distinguished Researcher Award from Asia Pacific Society on Computers in Education (APSCE) in 2022. Professor Chang is now Vice President (2022~) of International Association of Smart Learning Environments (IASLE), Executive Committee member of Asia-Pacific Society for Computers in Education (2017~2024, APSCE), Global Chinese Society for Computing in Education (2016~2025, GCSCE), and IEEE Computer Society Technical & Conference Activities Board. He is editors-in-chief (2019~) of Journal of Educational Technology & Society (Open Access SSCI), International Journal of Distance Education Technologies (Open Access ESCI, SCOPUS, EI), and Bulletin of Technical Committee on Learning Technology (Open Access ESCI). Professor Chang has given more than 155 talks and published more than 250 conference papers, journal papers, and book chapters.
While the generative AI (e.g., ChatGPT) is now well-known and popular with the public, the dataset used for training the generative AI is currently too broad to be helpful for teaching and learning. Moreover, the dataset used for training the generative AI has not been entirely vetted by experts — for instance, 60% of the dataset used for training the ChatGPT model comes from the Internet directly. This has important, understudied implications for both educators and learners who might wish to use generative AI tools. I will start this talk by summarizing the opinions and perceptions that educationists and researchers have on ChatGPT's deficiencies, found failures, challenges and risks. I will explain and show audience in the second part of the talk how non-tech savvy teachers can also adopt and use ChatGPT in their courses to design and create pedagogical agent that helps their students learning and practicing. Last but not least, many teachers might have concerns about their students using ChatGPT to write assignments instead of doing so on their own. At the end of this talk. I will introduce our research group's latest research, Authorship Forensic, that can correctly distinguish the works generated by ChatGPT 3.5, ChatGPT 4, and human authors with high precision rate (i.e., not mis-pointing finger on human authors and incorrectly labelling their works as AI-written ones) 98.06% and F0.5 score 0.96 in our preliminary study.
Rahmat Budiman started taking up his office as the Vice Rector for Institutional Development and Partnership Affairs of Universitas Terbuka (UT) since 2021. In addition to serving as the UT's Vice Rector, he is also concurrently serving as the Secretary-General of the AAOU.
As the Secretary-General of the AAOU, Dr Budiman is responsible for running the administrative, technical, financial and organization work of the association. Various initiatives and innovations have been introduced to foster distance learning. Recently, a book entitled Open and Distance Education in Asia was published as an initiative to show how distance teaching universities in Asia emerged, developed, and gained their reputations. As a distance teaching practitioner and enthusiast, he dedicates his research and teaching to develop and foster distance learning in Indonesia in particular and in Asia in general. His research interests include student services, teaching assistance, and distance language teaching. Several publications, including book chapters, proceedings, and journal articles have been published. The most recent articles published were “The digital literacy of first-year students and its function in an online method of delivery” (AAOU Journal in 2023) and “Self-efficacy of students taking the English Writing 3 course in an online learning setting” (Jurnal Pendidikan Terbuka dan Jarak Jauh, 2023). With his propositional knowledge and professional experience in distance learning, Rahmat Budiman continues to promote, thrive, and disseminate distance learning, both theories and practices.
The COVID-19 pandemic has accelerated the global trend towards distance learning, and Asia has witnessed a significant increase in the number of universities delivering their programs exclusively through distance education. This keynote speech will explore the factors driving this phenomenon and the implications for the future of higher education in Asia.
Starting with the data from an Asian Development Bank report, the speech will examine the rapid growth of distance education universities across Asia. It will then delve into the two key factors contributing to this trend: the pandemic's impact on the shift to remote learning and the regulatory changes in countries like Indonesia that have facilitated the establishment of distance education programs.
The presentation will also discuss the unique characteristics of Asia, such as its large and growing population and the concentration of the world's “mega-universities” in the region. These factors suggest that distance education will play an increasingly crucial role in providing access to higher education and meeting the demand for skilled labour.
Finally, the speech will address the critical question of quality in distance education. It will introduce three key initiatives to ensure the development of high-quality distance education institutions, including the establishment of an international accreditation system, the promotion of cross-border collaboration, and the creation of a dedicated world university ranking for distance education institutions.
Dragan Gašević is Distinguished Professor of Learning Analytics and Director of Research in the Department of Human Centred Computing of the Faculty of Information Technology and the Director of the Centre for Learning Analytics at Monash University. Dragan's research interests center around data analytic, AI, and design methods that can advance understanding of self-regulated and collaborative learning. He is a founder and served as the President (2015-2017) of the Society for Learning Analytics Research. He has also held several honorary appointments in Asia, Australia, Europe, and North America. He is a recipient of the Life-time Member Award (2022) as the highest distinction of the Society for Learning Analytics Research (SoLAR) and a Distinguished Member (2022) of the Association for Computing Machinery (ACM). In 2019-2022, he was recognized as the national field leader in educational technology in The Australian's Research Magazine that is published annually. He led the EU-funded SHEILA project that received the Best Research Project of the Year Award (2019) from the Association for Learning Technology.
Learning analytics is a well-established field that aims to make use of vast amounts of digital data to understand and enhance learning and teaching practices. The rise of generative artificial intelligence (GenAI) has sparked discussions about the synergy between GenAI and learning analytics. This talk will explore this synergy, specifically focusing on two areas. First, we will explore how GenAI creates a new education context. Learning analytics can offer valuable approaches to assess the effectiveness of GenAI in this new context. By leveraging learning analytics, we can ensure GenAI is utilized effectively in education. Second, we will investigate how GenAI technologies themselves can drive the development of even more powerful learning analytics. The talk will be grounded in findings from numerous empirical studies with direct implications for learning and teaching practice.
