Kuan-Chou Chen
Purdue University Northwest, USA

Professor Kuan-Chou Chen is Thomas M. McDermott Sr. Endowed Chair Professor in Economic Development, Professor of Management Information Systems. He was the Associate Dean for Graduate Studies, the Associate Dean for Faculty and Students Research, the Director of the White Lodging School of Hospitality and Tourism Management (2018-2019), Department Head of Information Systems, Finance, and Business Analytics (2005-2016), as well as Interim Department Head of Department of Graduate Studies in Education (2013-2014) at Purdue University Northwest. He was awarded with the “Outstanding Administrative Leadership award” for the year 2019-2020 at the University level. He received his Ph.D. from Michigan State University and his MBA from National Cheng-Kung University in Taiwan. He specialized in business intelligence, system simulation, project management, decision support systems, data mining, system analysis and design, e-business strategy and application, supply chain management, network design and security, knowledge management, and information economy. Professor Chen has more than 100 scholarly publications, most in peer-reviewed journals. He is an active participant in several professional journals and serves on three paper reviewer boards. Currently he is an Editor-in-Chief of International Journal of e-Education, e-Business, e-Management and e-Learning. His productivity and scholarship have been recognized by his colleagues, being nominated three years in a row for an “Outstanding Scholar Award.” He also the recipient of Teacher of the Year Award (Purdue University Northwest, 2005.

 

Title: Building an Adaptive Learning System with Implication for e-Learning

Abstract: E-Learning is the learning that involves interaction between a learner and a digital environment. It may incorporate text, graphics, narration, sound effects, music, video, and animation to enhance the learning experience. There are also many different elements that can make up an e-Learning program, such as live or pre-recorded lecture content, video, quizzes, simulations, games, activities, and other interactive elements. In general, instructors develop the presentation of learning materials according to students' weaknesses, as indicated by their responses to questions. The motivation is to allow e-Learning to incorporate the value of the interactivity afforded to a student by instructor.

Adaptive learning is an instructional method which uses digital tools as interactive teaching devices. Instructors use digital tools adapt to the learning needs of learners, helping them understand the underlying concepts quickly and efficiently. Thus, adaptive learning is viewed as stimulation to support learning and improve student engagement, so designing appropriate adaptive learning environments contributes to personalizing instruction to reinforce learning outcomes.

The purpose of this presentaiton is to design an adaptive e-learning system based on students' learning styles and study the impact of the adaptive e-learning environment on students’ engagement. The proposed adaptive e-learning system can help e-learning institutes in designing and developing more customized and adaptive e-learning environments to reinforce student engagement.

Keith Morrison
University of Saint Joseph, Macau, China

Professor Keith Morrison has worked in higher education for over 40 years, in the UK and South-East Asia, and, since 2000, in Macau, where he is currently Vice-rector for research at the University of Saint Joseph. He is the author/co-author of 20 academic books, including 8 editions of Research Methods in Education, and he has been the Co editor of the international peer reviewed journal Educational Research and Evaluation. He is in the top 20 of the world’s most cited authors in education, in Google Scholar. He has conducted consultancies for governments, companies, organizations and institutions in countries across the world. His most recent jointly authored book (2023) is Student Engagement, Higher Education, and Social Justice (with Corinna Bramley).

Title: Educational Technology and Student Engagement

Abstract: This keynote locates educational technology and its impact within current trends in higher education, raising questions for the partner of education technology, which is student engagement. However, ‘student engagement’ is a slippery term, asking ‘engagement in what, for what, and for whom?’. The keynote introduces implications of these questions for educational technology. In doing so, it provides a typology of studies in student engagement, drawing on the early work of Jürgen Habermas. This typology is then matched to how educational technology serves different interests in student engagement, moving beyond technicist and instrumentalist views of engagement, to engaging students in understanding, to a transformational, emancipatory role in which students take existential control of their own lives, agendas, and futures within a free, open, egalitarian society. From this, challenges are identified for educational technology in engaging students’ different interests, agendas and values, and the talk identifies key questions in meeting these challenges.

Cheng Siong Lee (Vincent)
Monash University, Australia

Cheng Siong Lee, Vincent (PhD 1992, University of Newcastle, NSW, Australia) is currently a top Level D1 Associate Professor with the Department of Data Science & Artificial Intelligence, Faculty of IT, Monash University, Australia. He is a Fellow of Institute of Engineers, Australia and a senior member of IEEE (USA). He has reserved as Deputy Research Director, Monash University; Academic Board, Monash University, Discipline leader for Telecommunication and Electrical Engineering, Swinburne University. He was the sole recipient of 2016 Dean of FIT (Monash University) award for excellence in Higher Degree Supervision. He has completed supervision of 30 PhD theses.

Lee’s research and higher education teaching span multi-disciplinary domains across IT, Digital Health, Signal and Information Processing, Financial Engineering (FinTech), wireless communications, Cryptography techniques for information and computer security, Educational Data Mining (with learner-centric education technology tools), Explainable AI, Deep ML, Computer Vision for dynamic objects tracking, and Multi-agent Autonomous Systems. Lee has published 200+ research papers in IEEE/ACM/Civil and Structural Engineering SCImago ranked Q1 Journals with High Impact factors (IEEE Transactions of Signal Processing, IEEE TKDE, IEEE Selected Area in Communications, Neurocomputing, Expert Systems with Applications, European Journal of Operational Research, Automation in Construction, Computer-aided in Civil and Infrastructural Engineering, Building and Construction Materials, Structural Health Monitoring, Neurocomputing, Information Processing and Management, Measurement; and in CORE A/A* Peer-review International Conferences proceedings (AAAI, IJCAI, IEEE ICDM, NeurIPS, CVPR, ICWS, ICDE, ICML, ACM KDD, PAKDD, CIKM, WWW, IEEE IC Signal Processing, IC-EDM). Lee also served as invited keynote speakers for a number of these IEEE and ACM Flagship conferences’ and General Chair and Co-chair of technical program committees.

Lee has been appointed and served as independent assessors for more than 50 national and international research council grant proposals in Australia (ARC), Singapore (NSF), and China (NSF). He has examined 30 External PhD theses for universities in Singapore, and Australia; as well as 10 Doctor of Business Administration theses for universities in Asia.

Title: Generative AI for Teaching and Learning: Issues, Challenges and Opportunities

Abstract: Generative AI has attracted intensive research and development in for cost effective operation in business enterprises recently. GPT AI, in particular Chat GPT4 is an effective education tool. It can be used to overcome three barriers to teaching and learning (including blended mode) in the face-to-face classroom: improving transfer, breaking the illusion of explanatory depth, and training learners to critically evaluate explanations. This talk provides background information and techniques on how GPT AI can be used to overcome the three barriers and includes prompts and assignment tasks design that teachers in universities and high schools can incorporate into their teaching and evaluation of assignments with on the fly feedback to students. I shall also cite some use cases on the use of prompts.