Title: Future of Open and Distance Learning within the Context of Emerging Trends in Higher Education and Generative-AI 

Abstract: The landscape of higher education is rapidly evolving and influenced by shifts toward competency-based learning, internationalization, and a stronger focus on career-ready education. This presentation explores the future of open and distance learning (ODL) in the context of these emerging trends and the profound impact of artificial intelligence (AI). The integration of competency-based learning frameworks within ODL platforms is reshaping educational assessment, focusing on skill mastery and practical outcomes rather than traditional time-based metrics. This approach aligns with the growing demand for career-ready education, preparing students more effectively for professional environments through tailored practical experiences, and direct industry involvement. Furthermore, the trend of offering micro-credentials and nano-credentials reflects a shift towards modular education, allowing students to acquire specific skills and knowledge rapidly and on-demand, enhancing their ability to adapt to changing job markets. Additionally, shared services in higher education, through collaborations between institutions, optimize resource use and expand educational offerings, drive down costs and increase accessibility. Internationalization is another critical trend, with institutions expanding their reach to offer global learning opportunities that enhance cultural competency and operate across borders supported by ODL systems. These systems are increasingly powered by Generative-AI technologies, which not only automate administrative tasks, but also enhance learning experiences through personalized learning paths, adaptive learning environments, and AI-driven simulation models, which provide immersive learning experiences that are both scalable and impactful. The convergence of these trends with AI technology signifies a transformative era in higher education, where learning is more accessible, flexible, and aligned with the global industry and societal needs.

 

BIO: CENGIZ HAKAN AYDIN, PhD, is a full professor in ANADOLU UNIVERSITY of TURKEY where he has been offering courses in the field of open and distance learning (ODL) since early 1990s. He is currently the Head of the Distance Education Department, Faculty of Open Education, ANADOLU UNIVERSITY, and the director of ANADOLU UNIVERSITY’s OpenAnadolu Project (including AKADEMA, MOOCs platform). Dr. AYDIN served as an instructional designer in the Open Education System until September 2017 and as Dean of the Faculty of Economics, one of the three faculties that made up the Open Education System of the University, between 2013 and 2016. His current research interests include the design and development of ODL environments, integration of new technologies (AI, VR, AR, MR, etc.) into ODL, Open Educational Resources (OERs), Open Educational Practices (OEPs), Massive Open Online Courses (MOOCs) and current trends in higher education. Dr. AYDIN has served as the International Chair and Board Member of the Association for Educational Communications and Technology (AECT), as a board member of the International Council for Educational Media (ICEM), and as a member of the Open Educational Resources Committee (OER Advocacy Committee) of the International Council for Distance Education (ICDE). He is currently a steering committee member of the OpenupEd initiative of the European Council for Distance Teaching Universities (EADTU), board member of the Association for Educational Communications and Technology (AECT), and member of the Centre for Distance Education Research (COER). He is also on the editorial boards of the International Review of Research in Open and Distance Learning (IRRODL), Educational Media International (EMI), and Journal of Open, Distance, and Digital Education (JODDE).

 

 

Title: Revolutionizing Education with Pedagogical AI Agents  

Abstract:In the age of Large Language Models (LLMs) and generative AI, educators must harness the potential of pedagogical AI agents to enhance their teaching practices. By mastering the design and deployment of these agents, teachers can tailor learning experiences to suit diverse student needs, guided by established learning theories and adaptive strategies. This approach not only facilitates personalized learning but also underscores the enduring importance of human teachers amidst the transformative impact of AI on education.

A key strength of LLMs lies in their ability to comprehend human language with depth and nuance, facilitating logical reasoning, planning, and execution of tasks. This capability has led to the assertion that anyone can become a programmer in the AI era. It empowers human teachers to collaborate with AI counterparts in crafting lesson plans using natural language. While human teachers focus on designing meaningful pedagogical content, AI agents assume the role of executing learning activities outlined in these plans. Acting as proxies for human teachers, AI agents extend the reach of teaching beyond physical constraints, enabling ubiquitous learning experiences.

In this presentation, I will delve into the conceptual framework and design principles for developing pedagogical AI agents. Through live demonstrations, I will showcase the versatility of these agents using a universal client, which leverages robotic interfaces and general-purpose computing devices, such as tablets or computers.

 

BIO:Dr. Nian-Shing Chen is a Chair Professor in the Institute for Research Excellence in Learning Sciences and Program of Learning Sciences at the National Taiwan Normal University, Taiwan.

Professor Chen received the National Outstanding Research award three times in 2008, 2011, and 2015. He is ranked in second place on the Top Authors list by article count in Computers & Education. He is ranked number 4 on the top scholar list in the educational technology field based on an article published in the British Journal of Educational Technology. One of his papers published in Innovations in Education and Teaching International was awarded as the top-cited article in 2010.

Professor Chen is ranked third in the list of Social Sciences and Humanities Scientists in Taiwan. Based on AD Scientific Index 2023, Prof. Chen is ranked number 8 in Asia and is ranked number 103 in the world in Education Research. He is listed as World’s top 2% scientists in 2021, 2022, 2023 and in the list of “Lifelong Science Influence Rankings (1960-2022) by Stanford University.

Professor Chen was served as the Editor-in-Chief for Educational Technology & Society (ET&S) journal. He is also a golden core member of IEEE, a lifelong member of ACM, and the former Chair of the IEEE Technical Committee on Learning Technology.

 

 

Title: The Potentials of Applying Multimodal Learning Analytics for Computer-Supported Collaborative Learning Process  

Abstract:In recent years, Computer-Supported Collaborative Learning (CSCL) designs have been widely used in formal and informal learning environments. How to analyze and scaffold CSCL processes, and to further improve and optimize the performances and efficacies of both students and teachers in CSCL is one of the most essential foci of CSCL research field. Advances in innovative technologies, such as data mining, deep learning and particularly Generative Artificial Intelligence (GAI), have offered more computational models and methods of learning analytics for CSCL processes. Therefore, this report will introduce a conceptual model and diverse empirical studies conducted in multiple disciplines and scenarios to elaborate the potentials of applying multimodal learning analytics for CSCL. Furthermore, the opportunities and challenges of using multimodal learning analytics in other hybrid learning activities will be also discussed.

 

BIO:Yanyan Li is a professor at the Faculty of Education, Beijing Normal University, China. She received her PhD degree of Computer Software and Theory from the Institute of Computing Technology, Chinese Academy of Sciences. She was the visiting scholar at the School of Computer Science, Carnegie Mellon University and the School of Education, the University of Hong Kong. Her research interests include AI in education, learning analytics, computer supported collaborative learning and STEM. She is the principal investigator (PI) of projects funded by the key research and development project of Ministry of Science and Technology, the National Natural Science Foundation of China, National Social Science foundation of China, and Key Project of Beijing Educational Science “Thirteenth Five-Year Plan”. She has published five academic books and more than 100 articles both in journals and international conferences covering interdisciplinary areas, e.g., computer science, learning science and educational studies. She is the current executive editor of Journal of Computers in Education and serves as editorial board member of the Journal of Smart Learning Environments. She was the invited keynote speaker of the 19th AIED(London), 13rd ICETC(Wuhan), 3rd CSTE(Beijing).