Speaker
Description
This study investigates AI anxiety (AIA) among higher education faculty in Japan using a bilingual adaptation of the AI Anxiety Scale (AIAS; Wang & Wang, 2022). An online survey was distributed to faculty at universities across Japan. Preliminary findings establish a baseline measurement of AIA in the Japanese higher education context and explore demographic factors associated with anxiety levels, offering implications for institutional AI policy and faculty development.
Abstract section 2: Contribution/research questions
- To what extent do university faculty in Japan experience AI anxiety?
- Are demographic factors—such as gender, years of teaching experience, or academic discipline—associated with differences in AI anxiety levels?
These questions aim to establish the first quantitative baseline of AIA among Japanese higher education faculty and identify groups that may benefit most from targeted institutional support.
Abstract section 1: Relevance
The rapid integration of Generative AI (GenAI) into higher education presents both opportunities and challenges for university faculty. While GenAI has the potential to enhance teaching efficiency, faculty may experience AI anxiety (AIA)—defined as an affective response of fear or unease that inhibits engagement with AI technologies (Wang & Wang, 2022). In Japan, universities are increasingly encouraged to develop AI usage policies amid growing student adoption of GenAI. Despite expanding international research on faculty AI attitudes (Banerjee & Banerjee, 2023; Xie et al., 2024), no study has established a baseline measurement of AIA among Japanese university faculty.
Abstract section 3: Content/method
The AIAS (Wang & Wang, 2022) was translated and validated in Japanese for this study. A bilingual (Japanese and English) online survey was distributed to faculty across higher education institutions in Japan. Quantitative data were analyzed using IBM SPSS to measure AIA levels and examine demographic variables. All procedures received IRB approval, and informed consent was obtained from all participants.
Abstract section 5: References
Banerjee, S., & Banerjee, B. (2023). College Teachers’ Anxiety Towards Artificial Intelligence: A Comparative Study. RESEARCH REVIEW International Journal of Multidisciplinary, 8(5), 36–43. https://doi.org/10.31305/rrijm.2023.v08.n05.005
Wang, Y., & Wang, Y. (2022). Development and validation of an artificial intelligence anxiety scale: an initial application in predicting motivated learning behavior, Interactive Learning Environments, 30:4, 619-634, DOI:10.1080/10494820.2019.1674887
Xie, Qin, Li, Ming, & Enkhtur, Ariunaa. (2024). Exploring Generative AI Policies in Higher Education: A Comparative Perspective from China, Japan, Mongolia, and the USA. 10.13140/RG.2.2.33314.03522.
Abstract section 4: Outcomes/results
Preliminary survey data reveal measurable levels of AI anxiety among Japanese university faculty, with variation across respondents. Initial analysis suggests that AIA is present across demographic groups and disciplines, consistent with findings from comparable international research (Banerjee & Banerjee, 2023). These preliminary results provide an initial baseline measurement of AIA in the Japanese higher education context. At the poster session, detailed findings—including demographic comparisons—will be presented alongside implications for university AI policy development and the design of targeted faculty support interventions.
| Title | AI Anxiety Among University Faculty in Japan: Early Findings |
|---|---|
| Teaching Context | College and university education |