Keynote Speakers_2025
Speaker: Assoc. Prof. Montathar Faraon
Affiliations: Kristianstad University, Sweden
Assoc. Prof. Montathar Faraon
Biography: Associate Prof. Montathar Faraon is an interaction design researcher at Kristianstad University, Sweden. He received his PhD in Information Society from Stockholm University, Sweden in 2018. His research focuses on generative artificial intelligence in higher education, interaction design, and digital transformation. Dr. Faraon has published in high-impact peer-reviewed journals such as Education and Information Technologies, E-learning and Digital Media, and International Journal of Technology and Design Education. His recent work examines ChatGPT adoption factors among Nordic and American university students, and how AI can support design students’ creativity in divergent and convergent processes. Dr. Faraon has authored several books on web development and has received multiple scientific awards.
Speech Information
Abstract:The evolution of artificial intelligence (AI) has triggered a shift in higher education that echoes past technological disruptions. Just as calculators, search engines, and digital encyclopedias transformed learning environments, generative AI now presents both opportunities and challenges in academia. Current AI services operate primarily within a transactional paradigm and are designed to perform tasks such as defining concepts, generating content, or processing data. These services have shown their usefulness for lower-order cognitive operations on Bloom's digital taxonomy. However, as we move up from the lower cognitive levels toward the higher cognitive processes, we encounter limitations of transactional AI services. Transactional services prove particularly inadequate when confronting "wicked problems" in educational contexts, i.e., challenges that lack definitive formulations or solutions, exist in unique contexts, and resist simple classification as right or wrong. The trajectory of AI in higher education appears to be advancing toward relational AI services that establish contextually aware, value-sensitive connections with teachers and students. Such relational services may transcend the constraints of transactional AI by taking into consideration individual values, learning styles, contextual understanding, and emotional intelligence to further higher-order thinking abilities among students.
Speaker: Prof. Hui-Wen Huang
Affiliations: Shaoguan University, China
Prof. Hui-Wen Huang
Biography: Dr. Hui-Wen Huang is a professor in the College of Education at Shaoguan University, Guangdong, China. She completed her Ph.D. degree in curriculum and instruction with a focus on online education from the University of Idaho, U.S.A. Prior to her current position, she had worked in various universities, including Taiwan, the U.S., and Mainland China, as a faculty member in teaching and research over the past two decades. Her recent work involves immersive learning using 360 VR videos across disciplines and artificial intelligence (AI) in education. Dr. Huang has published more than 30 SSCI-indexed journal articles and international conference proceedings indexed by EI Compendex on educational technology, technology-supported mental health, and human-AI interactions. She has actively served the academic communities, either as an invited speaker or technical committee member, in different international conferences over the past five years. She has been working with different scholars in Japan, Australia, and the U.S. to help EFL learners develop cross-cultural competence since Spring 2020. Recently, she is working on applying AI technologies in education and psychology.
Speech Information
Abstract:This study compares the effectiveness of AI-guided meditation and text-based meditation for emotion regulation by analyzing the alpha-theta ratio (ATR) in electroencephalography (EEG) data. Both EEG recordings and post-task interviews were utilized to address the research questions. A total of 23 participants (aged 19–21) were randomly assigned to either the AI-guided or text-based meditation group. Alpha-theta cross-frequency dynamics, a recognized neurophysiological marker of meditative states, were examined. The AI-guided meditation group engaged with Doubao, a locally developed AI chatbot in China.
Results indicated significant differences in ATR between the two groups, with the AI-guided meditation group exhibiting lower ATR values. According to existing literature, lower ATR is associated with deeper meditative states and increased relaxation. Qualitative interview findings further suggested that AI-guided meditation effectively supported internal attention and emotion regulation. However, two participants noted that the chatbot’s tone felt less emotionally engaging compared to human-led or video-based meditation formats.
In educational contexts, the findings highlight the potential of integrating AI-guided meditation as a low-cost, accessible tool to support students’ emotional regulation, focus, and stress management. Incorporating such interventions into learning environments—particularly in high-pressure or emotional demanding academic settings—may enhance students’ cognitive readiness and overall well-being, ultimately contributing to more effective learning outcomes.
Speaker: Prof. Fahim Khan
Affiliations: Toyo University, Tokyo, Japan
Prof. Fahim Khan
Biography: Dr. Fahim Khan is a Professor at the Department of Information Networking for Innovation and Design (INIAD) in Toyo University, Tokyo, Japan. Prior to joining Toyo University, he served as a faculty member at the University of Tokyo, from where he also obtained his MS and PhD in Applied Computer Science. His recent research encompasses several avenues of applied computing, including: developing security measures for IoT and smart spaces; designing distributed systems using machine learning, GenAI, and blockchain; and leveraging EdTech and learning sciences for CS, STEM and SDGs education. His research publications have won multiple best paper awards at IEEE conferences. He actively serves as a committee member at numerous IEEE and ACM conferences. A Senior Member of IEEE, Khan is a recipient of IEEE Japan Medal. He is also a globally selected member of ACM Future of Computing Academy (ACM-FCA), an initiative that brings together next-generation leaders in computing to carry the computing community into the future.
Speech Information
Abstract:This talk examines the potential of Generative Artificial Intelligence (GenAI) to reshape educational practices by enabling personalized learning pathways, broadening access to high-quality education, and enhancing the capacity of educators to develop dynamic and interactive instructional materials. As a driver of innovation and inclusivity, GenAI offers promising solutions to longstanding challenges within contemporary educational systems. Yet, these prospects are accompanied by significant ethical and practical concerns. While there are well-known GenAI challenges regarding hallucination, data privacy and algorithmic bias, this talk will critically engage with the potential diminishment of critical thinking skills among learners due to irresponsible use of GenAI. The latter portion of the presentation will highlight a case study from an active research initiative, illustrating how multimodal GenAI can be effectively employed in self-directed, inquiry-based programming instruction—balancing cost-efficiency with pedagogical integrity. In a nutshell, rather than advocating for wholesale adoption or rejection, the objective is to consider how GenAI's capabilities can be responsibly harnessed to foster equitable, empowering, and high-quality educational opportunities.