Abstract. This study explores teacher agency and strategies for extending teacher agency to meet the challenges brought about by the rapid Artificial Intelligence (AI) advancements. It adopts the concept of teacher agency, rather than competency for teachers, to explore the complexities of teacher professional development. It builds upon the growing body of research that explores teacher agency through a systems approach, emphasizing the interdependent, interactive and evolving nature of teacher agency. Using the UNESCO’s AI competency framework as a foundation, this research investigates the current state of AI-empowered teaching practices in vocational colleges and schools in China. By analyzing empirical data from a survey, it provides insights into how teachers engage with AI technologies at different agency levels—ranging from basic adoption to pedagogical innovation and leadership in shaping AI-empowered education. The study underscores the importance of a human-centered mindset to AI in education, an approach which ensures that teachers retain agency while leveraging AI to innovate student learning experience and teachers’ life-long professional development. Based on its findings, the study proposes strategies for expanding teacher agency at various stages of growth. These include equipping educators with AI knowledge and application skills, fostering awareness of the ethical and sociocultural implications of AI, deepening pedagogical strategies for meaningful AI integration, and promoting continuous professional development through AI-powered tools.
Dr. Xibin Han is a professor of Educational Technology at Tsinghua University's Institute of Education, specializing in blended learning theory, AI-empowered pedagogy, and data-driven learning analytics. With over 100 peer-reviewed publications and 10 academic monographs, his research has significantly advanced the integration of emerging technologies in higher education and vocational training systems. A recipient of Elsevier's "Most Cited Chinese Researcher" (2020) and 20+ national research/teaching awards, Professor Han has held key leadership roles including Vice Dean of Tsinghua's Institute of Education (2009-2023) and President of the Society for International Chinese in Educational Technology (SICET, 2018). His expertise extends to policy consultation for China's Ministry of Education on ICT-based education innovation and UNESCO's Asia-Pacific Blended Learning Capacity Building Project (2015-2017). Currently co-editor of the Journal of Educational Technology Development and Exchange (JETDE), he previously contributed to the editorial board of the Internet and Higher Education Journal.
Abstract. Higher education in Indonesia is facing the challenge of producing graduates who are not only academically competent but also equipped with practical skills relevant to the demands of Industry 4.0. To address this, student-centered learning has been promoted to enhance 21st-century skills such as critical thinking and problem-solving. In this context, Generative AI presents a promising tool to support learning and research activities, helping students design survey instruments, analyze data, and structure research reports more efficiently. Despite growing interest in the technical and pedagogical aspects of Generative AI, few studies have examined its impact on students' quantitative research skills and research self-efficacy. This study integrates Generative AI into research-based learning within an Applied Statistics course, implementing the 5E Learning Model (Engage, Explore, Explain, Elaborate, Evaluate) with ChatGPT as a learning aid. Using the DeLone & McLean model, Technology Acceptance Model, and Rational Choice Theory, this research explores students’ perceptions, adoption drivers, and the perceived impact of Generative AI on research performance. Data collected from 219 undergraduate students indicate that perceived usefulness, ease of use, and satisfaction significantly influence students’ intention to adopt Generative AI, while perceived risk and learning cost do not. Moreover, Generative AI usage contributes positively to students’ research performance, including improved output quality, enhanced research skills, greater self-confidence, and a stronger intention to undertake a research project for graduation. These findings not only enrich the literature on educational technology adoption but also offer practical insights for integrating Generative AI into higher education curricula to support digital transformation in learning
Prof. Dr. Achmad Nizar Hidayanto is a Professor at the Faculty of Computer Science, Universitas Indonesia (UI). He is currently the Vice Dean for Resources, Venture, and General Administrations at the Faculty of Computer Science, UI. He graduated his BSc, MSc, and PhD in Computer Science from Universitas Indonesia.
During his career, Dr. Hidayanto was appointed in some positions such as: Head of Data Processing of the National Entrance Test for University, IT Manager, Head of IS/IT Program Study (undergraduate and master degree), etc. In addition, since 2014, Dr. Hidayanto has been the Head of Research and Strategic Planning in the Indonesia Association of Higher Education in Computer Science. He was also involved as a resource person in some Indonesia government institution, for example the Ministry of ICT for formulating the roles of Government CIO in Indonesia, the Agency for National Standard of Education for formulating the standards for computer-based testing and research and community engagement outputs evaluation, the Agency for National Development for formulating data management practice in Oen Data initiative, etc.
Dr. Hidayanto research interests are in Information Systems area, particularly related to e-government, e-commerce, e-health, human behavior and IT adoption, and IT management. He has published more than 450 papers in international conferences/journals, among of them are International Journal of Information Management, Expert Systems with Applications, Pacific Asia Journal of the Association for Information Systems, IEEE Access, International Journal of Medical Informatics, Transforming Government: People, Process, and Policy, Journal of Information Technology Education: Research, Journal of Theoretical and Applied Electronic Commerce Research, etc. He and his colleagues won best paper award some conferences such as: IADIS International Conference Web Based Communities, International Conference Advanced Computer Science and Information Systems (ICACSIS), International Conference on Informatics and Computing (ICIC), International Conference on Information Management and Technology (ICIMTECH), International Conference on Computing Engineering and Design (ICCED), International Conference on Web Based Communities and Social Media, and Technology, Innovation and Industrial Management International Conference (TIIM), IADIS International Conference on e-Society.
Abstract. As Thailand navigates the challenges of the digital economy, higher education institutions are increasingly compelled to undertake systemic transformation to prepare graduates for employment in AI-integrated environments. This study proposes an AI-driven institutional transformation model specifically tailored to the context of Thai universities. The study was conducted with three primary objectives: (1) to synthesize the core components of the model, (2) to develop and validate the proposed framework, and (3) to assess its practical applicability. A mixed methods research (MMR) design was adopted to ensure conceptual rigor and contextual relevance. The research procedure comprised three phases: (1) model synthesis, (2) model validation, and (3) model evaluation. The findings revealed that the developed model, referred to as the 3D-POD Model, encompasses three integrated dimensions of transformation: 1) The vertical axis comprises five strategic domains—People, Pedagogy, Process, Platform, and Pathway; 2) The horizontal axis outlines five operational phases—Origin, Operation, Output, Outcome, and Optimization; 3) The depth axis defines five levels of digital maturity—Digital Passive, Digitization, Digitalization, Digital Transition, and Digital Transformation. Collectively, these dimensions form a structured matrix (5 Strategic × 5 Operational × 5 Maturity Levels) that provides a practical lens for planning, implementing, and assessing AI-enhanced transformation in higher education. Quantitative validation confirmed the model’s high content validity and practical applicability, offering a strategic roadmap for AI-enhanced transformation and graduate employability in Thai higher education. The 3D-POD model serves as a strategic roadmap to support institutional transformation and improve graduate employability in Thailand’s AI-driven educational landscape.
Dr. Sirinuch Sararuch is a highly respected leader in enterprise technology, bringing over 20 years of expertise in digital transformation, cloud computing, and strategic enterprise sales throughout the ASEAN region. She currently serves as the Sales Director for Education, Healthcare, and Public Sector at SAP Thailand and Indochina, where she drives initiatives that enable organizations to leverage data and AI-powered platforms for transformative innovation.
Renowned for her contributions to digital transformation in education, Dr. Sararuch has played a pivotal advisory role for several leading universities and has actively contributed to national education policy as a member of the Educational Technology Committee under Thailand's Ministry of Education. Her work has significantly influenced the strategic direction of educational technology both at the institutional and national levels.
She holds a Ph.D. in Information Technology for Education from King Mongkut's University of Technology North Bangkok, an MBA in Finance from the University of Wisconsin-La Crosse, and a BA in Economics from Thammasat University. Her distinguished career spans leadership roles at AWS, Microsoft, IBM, Oracle, and TmaxSoft, where she has successfully led large-scale digital transformation projects in the public sector and higher education.
In recognition of her impactful work, Dr. Sararuch received an Honorary Award from the Minister of Education in 2022 and was honored by the Thai Association of Educational Technology in 2023 for her outstanding contributions to the advancement of EdTech in Thailand.
Abstract. This talk examines the impact of artificial intelligence (AI) on language course design, highlighting both challenges and opportunities. I begin by addressing educators’ growing concerns about students’ potential misuse of AI in academic assignments, which has led to a shift towards more cognitively demanding assessment formats. These redesigned assessments encourage critical engagement with course materials, ensuring that students actively construct knowledge rather than passively relying on AI-generated responses. Next, I explore the integration of AI in feedback mechanisms, demonstrating how AI-driven feedback can streamline teachers’ workload while improving the quality, consistency, and timeliness of feedback on students’ writing and speaking. I discuss the synergy between teacher feedback, peer feedback, and AI-generated feedback, showing how this multi-faceted approach caters to diverse learning needs and enhances student development. Furthermore, I highlight the potential of AI to facilitate personalised learning experiences, fostering adaptive learning pathways that support students at different proficiency levels. Drawing on examples from English language curriculum design in higher education in Hong Kong, I illustrate how AI-driven tools can be effectively integrated into language instruction. This talk provides practical insights and strategies for educators seeking to harness AI’s potential to enhance language education, improve assessment authenticity, and support student success in an evolving academic landscape
Professor Zou Di is an Associate Professor in the Department of English and Communication and the Faculty of Humanities at The Hong Kong Polytechnic University. She holds a PhD in English from City University of Hong Kong and a TESOL certificate from Trinity College London. Her research expertise lies in educational technology, language education, computer-assisted language learning (CALL), game-based language learning, and artificial intelligence (AI) in language education.
With a strong research focus on educational technology in language education, Professor Zou has led and collaborated on over 20 research projects. She has published more than 200 research papers, primarily in SSCI- and Scopus-indexed journals, including Computers & Education, British Journal of Educational Technology, Computer Assisted Language Learning, Language Learning & Technology, and System. Her work has had a significant impact in the field, with a Google Scholar citation count of 9,408 (as of February 2025), an h-index of 46, and an i10-index of 95. She has been recognized as one of the World's Top 2% Scientists by Stanford University for four consecutive years (2021–2024). Several of her papers in Computers & Education and Computer Assisted Language Learning rank among the Most Cited Articles in their respective journals.
Professor Zou's contributions to teaching and research have earned her numerous awards. She has received the Excellent Paper Award from the International Conference on Blended Learning and the International Conference on Open and Innovative Education. Her innovative teaching projects have been recognized internationally, winning the Gold Medal and Special Awards at the International Invention Innovation Competition in Canada (iCAN) and the Silver Medal at the International Innovation and Invention Competition (IIIC) in Taiwan.
Beyond her research and teaching achievements, Professor Zou plays an active role in academic publishing. She serves as an Associate Editor for Computers & Education (SSCI IF=8.9), Computers & Education: X Reality, and previously for the Australasian Journal of Educational Technology (SSCI IF=4.1) (2021–2022). She is also an editorial board member for Educational Technology & Society (SSCI IF=4.7) and theInternational Journal of Mobile Learning and Organisation. Additionally, she has led special issues for several prestigious journals, including Computers in Human Behavior (SSCI IF=9.0), System (SSCI IF=4.9), Educational Technology & Society (SSCI IF=4.7), and Computers & Education: Artificial Intelligence (Scopus CiteScore=16.8).
Professor Zou's extensive research, editorial contributions, and dedication to technological advancements in language education continue to shape the field and inspire scholars worldwide.