Assoc. Prof. Zigang Ge
Beijing University of Posts and Telecommunications, China
Zigang Ge is an associate professor and academic adviser for MA and MS programs at the School of Humanities, BUPT. He was awarded the title of “Beijing Higher Education Young Elite Teacher” and the title of “Teaching Master for Integrating Morality Cultivation in Courses” by Beijing Municipal Government. He has published over 20 academic papers in authoritative and core journals both domestically and internationally including Computers & Education, Computer Assisted Language Learning, International Journal of Computer-Supported Collaborative Learning, Interactive Learning Environments, and Journal of Educational & Society. He has served as a member of the editorial board of The Journal of Asia TEFL, a technical committee member for international conferences such as International Conference on Signal and Image Processing (since 2019) and International Conference on Digital Technology in Education (ICDTE2023), and an external reviewer for academic papers at China Academic Degrees and Graduate Education Development Center.
Title: The Impacts of AI Literacy in K-12 Education
Abstract: As most teachers do not know how AI functions and cannot make full use of AI in education, there is an urgent need to investigate Chinese teachers’ intentions to learn AI and related determinants so as to promote their AI learning. This presentation includes the research model, which has been designed and validated based on existing literature to indicate and explain how teachers’ AI literacy has a direct impact on perceptions of the use of AI for social good, self-efficacy in learning AI and awareness of AI ethics and has an indirect impact on behavioral intentions to learn AI. This presentation could be indispensable for future researchers, academicians and practitioners in measuring the impacts of AI literacy in K-12 education.
Assoc. Prof. A.Y.M. Atiquil Islam
East China Normal University, China
Assoc. Prof. A.Y.M. Atiquil Islam is the Director of the
International Graduate Program in Educational Technology
at the Department of Education Information Technology of
the East China Normal University. He is also a Guest
Professor at the School of Teacher Education of Jiangsu
University. He obtained a multidimensional PhD degree by
combining two faculties, namely, Education and Computer
Science & Information Technology at the Institute of
Graduate Studies, University of Malaya. In his field of
specialization, he developed and validated three models,
namely, the Technology Adoption and Gratification (TAG)
Model, the Technology Satisfaction Model (TSM) and the
Online Database Adoption and Satisfaction (ODAS) Model.
Dr. Islam has had almost 20 years of experience in
academia, industry and business. Furthermore, Dr. Islam
has presented many papers at international conferences
(Japan, Singapore, China, Indonesia and Malaysia) and
published journal articles, books and chapters. One of
his articles was listed as a “Highly Cited Paper” in
Essential Science Indicators (ESI) in 2022 & 2023. He
has also delivered keynote addresses, speeches, and
guest lectures many times in the past five years. Dr.
Islam has published in the British Journal of
Educational Technology, Instructional Science,
Educational Technology Research and Development, Journal
of Information Science, Educational Psychology,
Interactive Learning Environments, Journal of Research
in Science Teaching, Online Information Review, and
International Journal of Technology and Human
Interaction. He serves as the Principal Investigator and
Co-Investigator of local and international research
grants totaling over a million yuan.
Dr. Islam has international collaboration with the
United States of America, the United Kingdom, Germany,
Australia, Malaysia, the Philippines, Pakistan,
Indonesia, Saudi Arabia, Algeria, Bangladesh and
Nigeria. Dr. Islam is an Editorial Board Member of the
British Journal of Educational Technology (Q1, SSCI,
2022 IF=6.6), Executive Editor of the International
Journal of Smart Technology and Learning, Editor of
Cogent Education (ESCI & Scopus), and Article Editor of
SAGE Open (Q2, SSCI, 2021 IF=2.032). His research
interests are in the arena of Assessment of Educational
Technology, ICT in Higher Education, Quantitative
Modeling, Artificial Intelligence, STEM Education, Human
Computer Interaction, Information Science, Digital
Library Sciences, Metaverse and Virtual Reality.
Title: Exploring the Impact of Different Types of E-learners’ Anonymity on Their Learning Engagement in Competitive Gamified Language Learning
Abstract: The present study aims to explore the impact of two types of e-learners’ anonymity on their language learning engagement in a 50-day competitive gamified English vocabulary learning process. The two anonymity types were full anonymity, which means the participants were anonymous to both their peers and the instructor in the learning process, and partial anonymity, which required the participants to be anonymous only to their peers. One hundred and eighty adult e-learners were recruited as the participants and randomly assigned into three groups, with one group adopting the full anonymity pattern, one group using the partial anonymity pattern, and a third group employing the non-anonymity pattern. An online pretest, an online posttest and two online questionnaires were used as the research instruments. The two tests were used to assess the participants’ learning performance. One questionnaire was to obtain the participants’ self-report values on three scales of learning engagement, namely behavioral engagement, emotional engagement, and cognitive engagement. The other questionnaire together with some interviews was applied to inquire about the participants’ attitudes towards anonymity in gamified learning. The results indicate that the full anonymity pattern exerted the most positive impact on the participants’ behavioral and emotional engagement, and this pattern also brought about the best learning performance on the posttest. However, the non-anonymity pattern outperformed the other two patterns on the cognitive engagement scale. Then the possible impact of anonymity on learning engagement and learning performance was discussed.
Assoc.
Prof. Yu-Mei Wang
University of Alabama at Birmingham, USA
Dr. Yu-mei Wang is a faculty member at the University of Alabama at Birmingham, where she teaches discussion-based online courses at both the undergraduate and graduate levels. Her research interests focus on new media literacy, technology proficiencies of digital natives as pre-service teachers, meaningful online discourse communities, and technology diffusion in teacher education programs. Dr. Wang has an extensive publication record in academic journals. Her new book, Online Discussion in Secondary and Higher Education: A Complete Guide to Building a Dynamic Online Discourse Community, was published in January 2024 by Springer.
Title：AI Diffusion in Teacher Education through the
Lens of Organizational Changes
Abstract: With the rapid evolution of AI impacting
every aspect of our lives, teacher education faces
several crucial questions: What skills do teachers need
to effectively use AI in teaching? How will teacher
education programs ensure their graduates acquire the
necessary skills to function effectively in AI-age
classrooms? More urgently, what challenges lie ahead in
successfully implementing AI diffusion in teacher
education? Faculty members play an essential role in
this process by reforming teacher education programs,
designing courses that integrate AI technologies, and
modeling the use of AI tools to benefit student
learning. To promote AI diffusion, an initiative was
launched at an urban university’ s school of education
in the United States during the 2023-2024 academic year.
The goal was to equip faculty members with essential AI
literacy skills, enabling them to leverage AI
technologies in preparing future teachers. However, the
initiative failed to motivate faculty members to
participate. This presentation will analyze the failed
AI initiative through the lens of technology diffusion
theories.