TIRF is pleased to share that a slidecast and the Mentimeter results from its session at the 2026 TESOL Convention are now available. The session, entitled “Unmasking AI: What Language Teachers Need to Know,” was delivered on March 25, 2026 in Salt Lake City, Utah, as part of TIRF’s ongoing collaboration with TESOL.

The presentation featured a distinguished group of speakers, including Dr. Onur Ural Burns (University of California, Riverside), Dr. Xiangying Jiang (Duolingo), Dr. Joyce Kling (TIRF), Dr. Nick Saville (TIRF), and Justin Shewell (TESOL International Association). Together, they explored practical and research-informed perspectives on artificial intelligence in English language teaching, engaging attendees in a dynamic and interactive discussion.

As in previous years, the session incorporated live audience polling using Mentimeter, allowing participants to share their views and experiences with AI in real time. The results provide a snapshot of current thinking across the field and highlight both opportunities and ongoing questions related to the use of AI in language education.

The slidecast—combining presentation slides with audio narration—along with a summary of Mentimeter responses, is now available via TIRF’s website. These resources are intended to extend the reach of the session beyond the TESOL Convention and to support educators, researchers, and policymakers interested in the evolving role of AI in language education.

Click here to access the slidecast. And click here to see a PDF of the Mentimeter results or see the following summary:

• Current Uses of AI: Participants most commonly reported using AI for lesson planning (41%) and producing authentic learning tasks (38%), followed by practicing interactive speaking (19%), with very limited use for assigning and scoring writing (3%).
• What Teachers Need to Learn: The strongest need identified was how to combine AI systems with human teaching practices (42%), followed by using AI in sustainable ways (26%), automating teaching practices (21%), and understanding how AI algorithms work (12%).
• Quality and Oversight: An overwhelming majority (91%) indicated that AI performance should be judged by whether output meets expert-quality standards, and 100% agreed that AI-generated content must be reviewed and refined by educators before use.
• Academic Integrity: Participants identified ease, fear, and pressure as key drivers of student cheating, and strongly supported assignment design approaches—such as personal reflection (avg. 4.6 out of 5) and process-focused work (4.4 out of 5)—over banning AI outright (1.5 out of 5).
• Institutional Context: A majority (57%) reported that their institutions do not yet have clear policies on AI use, while only 18% indicated AI is fully allowed for both students and educators.
• Skills for the Future: Critical thinking emerged as the most frequently cited skill for working effectively with AI, alongside growing attention to prompt design and awareness of AI’s limitations.

To learn more about TIRF’s AI activities, please click here. To learn about TIRF’s AI Show & Tell program, as well as join its upcoming webinar on this initiative, click here. Finally, note that additional TIRF presentations can be found on its website – click here to learn more.