Speakers
Abstract section 1: Relevance
AI in education has potential to improve the quality of education by personalizing learning experiences and catering to diverse student needs (World Economic Forum, 2024). Recent advances in agentic AI systems, which are capable of autonomous, multi-step task planning and execution (Gutowska, n.d.), empower educators to design ed tech programs tailor made to their learners’ needs and interests. A key question for practitioners is how can they leverage these AI tools in ways that adhere to time-proven effective principles of instructed second language learning (e.g. Ellis, 2014), including maintaining the important element of social interaction (e.g. Long, 1996, Gass, 2018).
Abstract section 2: Contribution/research questions
The purpose of this forum panel is to outline potential affordances of agentive AI tools by presenting the perspectives of instructor-researchers on areas of material design and creation, personalization of learning experience, expansion of opportunities for learning beyond the classroom, effective use of AI tools, and the changing nature of social interaction in language classrooms. Presenters will discuss implications for teaching practice and how instructors can engage in use of these tools most effectively.
Abstract section 3: Content/method
After brief framing remarks on agentic AI and language education, each panelist will share their insights on one theme: (1) social interaction in instructed second language acquisition; (2) personalization for self-regulated and autonomous second language learning; (3) the teacher as instructional designer/learning architect enabled by agentic tools; and (4) data-driven language teaching supported by AI analytics. Audience questions and cross-panel dialogue will conclude the session.
Abstract section 4: Outcomes/results
Participants will engage in a guided discussion of four classroom-relevant themes: (1) how teachers can intentionally design tasks that protect and promote meaningful social interaction when learners use agentic AI; (2) realistic uses and limits of AI-driven personalization for self-regulated and autonomous learning; (3) practical ways agentic tools can support teachers as instructional designers/learning architects (e.g., rapid prototyping of sequences, materials, and feedback tools); and (4) examples of data-informed teaching moves made possible through AI analytics. Attendees will leave with concrete activity ideas, questions to take back to their programs, and strategies for responsible classroom adoption.
Abstract section 5: References
Ellis, R. (2014). Principles of instructed second language learning. In M. C-M., D. B., and M. S. (Eds.), Teaching English as a second or foreign language (pp. 31-45). National Geographic learning.
Gass, S. M. (2018). Input, interaction, and the second language learner. Routledge.
Gutowska, A. (n.d.). What are AI agents? https://www.ibm.com/think/topics/ai-agents
Long, M. H. (1996). The role of the linguistic environment in second language acquisition. In W. R. and T. K. B. (Eds.), Handbook of second language acquisition (pp. 413-468). Academic Press.
World Economic Forum (2024). Shaping the future of learning: The role of AI in education 4.0. https://www.weforum.org/publications/shaping-the-future-of-learning-the-role-of-ai-in-education-4-0/
| Title | The Role of Language Teachers in the Age of Agentic AI |
|---|---|
| Teaching Context | General |