Opening AI for Language Learning

What does it really mean for a machine to "think"? In this episode, Mat and Phil explore the life and legacy of pioneering mathematician Alan Turing, whose work laid the foundation for modern computing and artificial intelligence. From the origins of the Turing Test to whether ChatGPT has truly passed it, the hosts unpack how Turing's ideas provide a valuable framework for thinking critically abou...

Exploring two contrasting perspectives on AI in education by Andreas Horn and Emily Bender, Mat and Phil reflect on AI’s promises and pitfalls, what artificial intelligence really means, and how language educators can respond thoughtfully to a technology that is already shaping education. In this episode: Both texts are available at https://unesdoc.unesco.org/ark:/48223/pf0000395236 (page numbers...

Mat and Phil welcome their first-ever guest, Glenn Stockwell, to discuss professional development, learner training, and the ethical, legal, and policy challenges of generative AI in language education. The conversation also explores AI literacy, academic publishing, the Gartner Hype Cycle, and emerging research on AI's impact on language learning. In this episode: Glenn Stockwell: https://www.edu...

In this episode, Phil reports to Mat on his adventures at the TESOL 2026 Convention in Salt Lake City, March 24-27. Phil talked with exhibitors and attended as many AI-focused presentations, panels, and posters as he could to get a sense of how AI, especially GenAI, is being presented by and to professional English language teachers. Mat comments on the value of panels and the conversations at con...

In this episode, Mat and Phil discuss a book chapter by Glenn Stockwell, in which he writes about professional development and learner training for AI, highlighting the importance of ongoing reflection, learning training, and documenting professional growth. Glenn is the editor in chief of the journal Computer Assisted Language Learning and a professor of Applied Linguistics at the Education Unive...

Language teachers can build their AI competence through the seven guiding principles of Sustained Integrated Professional Development. From starting small to taking a learner’s perspective, from reflecting critically to working with students and peers, as AI continues to evolve. In this episode: Principles of GenAI-SIPD by Phil Hubbard and Mat Schulze: https://www.igi-global.com/gateway/article/fu...

Mat and Phil return with six additional knowledge areas and skills that language teachers need to navigate AI thoughtfully, including course and lesson creation, assessment, and student misconduct, highlighting the importance of teacher awareness, transparency, and professional judgment in a rapidly evolving landscape. In this episode: Hubbard and Schulze (2025). AI and the future of language teac...

Learning about GenAI? Mat and Phil talk about the first four (of ten) knowledge areas and skills language teachers should aim to have now: prompting, ethics, chatbots, and translation. Combining practical examples with theoretical insights, they discuss these knowledge areas and skills in more detail than they could give in their paper: AI and the future of language teaching: Motivating Sustained...

What is a large language model (LLM), actually? How do these systems work? Why can they feel like human conversation partners, and why is that perception misleading? Mat and Phil open the podcast by answering these questions, and discussing the key implications for language teaching and learning. In this episode: Phil Hubbard: https://web.stanford.edu/~efs/phil/ Mat Schulze: https://PantaRhei.pres...