Speakers
Abstract section 2: Contribution/research questions
This study investigates how stakeholders in higher education interpret and navigate institutional AI policies. The research addresses the following questions:
1. How do faculty, preservice teachers, and policymakers understand the pedagogical implications of AI policies in higher education?
2. What governance and operational challenges influence the implementation of AI policies?
3. What implications do these interpretations have for language teaching and CALL practices?
Abstract section 3: Content/method
This qualitative study uses semi structured interviews with faculty, preservice teachers, and university policymakers. Interview data were analyzed using thematic analysis guided by Chan’s AI Ecological Education Policy Framework. The framework examines AI policy implementation across pedagogical, governance, and operational dimensions. Coding focused on identifying patterns in how participants interpret institutional AI policies, adapt teaching practices, and respond to the challenges created by generative AI tools in educational settings.
Abstract section 5: References
Chapelle, C. A., 2001, Computer applications in second language acquisition, Cambridge University Press.
Levy, M., Stockwell, G., 2013, CALL dimensions: Options and issues in computer assisted language learning, Routledge.
Chan, C. K. Y., 2023, A comprehensive AI policy education framework for university teaching and learning.
Abstract section 4: Outcomes/results
Findings show that AI policy implementation is shaped by tensions between encouraging innovative AI use and maintaining responsible academic practices. Participants emphasized the need for balanced AI integration, clearer institutional guidance, and professional development for educators. Results suggest that effective AI policies must address real classroom practices while supporting ethical and transparent AI use. For language educators, the findings highlight the importance of designing learning activities that integrate AI tools responsibly while maintaining meaningful language practice and learner engagement.
Abstract section 1: Relevance
Generative artificial intelligence is rapidly transforming language education by supporting writing, feedback, and language practice through tools such as ChatGPT. At the same time, universities are struggling to develop clear policies that guide responsible AI use in teaching and learning. Research in computer assisted language learning highlights both opportunities and challenges related to AI integration, including issues of academic integrity, ethical use, and pedagogical alignment (Chapelle, 2001; Levy & Stockwell, 2013). Understanding how educators interpret and implement AI policies is therefore critical for supporting effective and responsible AI use in language education contexts.
| Title | AI Policy Challenges in Language Education |
|---|---|
| Teaching Context | College and university education |