Opening AI for Language Learning

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 University of Hong Kong.

In this episode:

• Glenn Stockwell: https://www.eduhk.hk/en/experts/professor-stockwell-glenn
• Glenn Stockwell's chapter: Professional development and learner training. https://castledown.online/reference/9781763711600-12/
• The book with Glenn’s chapter: Yijen Wang, Antonie Alm, and Gilbert Dizon (Eds.), Insights into AI and language teaching and learning. Castledown Publishers. https://castledown.online/reference/9781763711600/
• Mat’s chapter in the same book: ICALL and AI: Seven lessons from seventy years. https://doi.org/10.29140/9781763711600-02

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/full-text-html/378304
• Darling-Hammond, L., Hyler, M. E., & Gardner, M. (2017). Effective teacher professional development. Learning Policy Institute. DOI: 10.54300/122.311 https://learningpolicyinstitute.org/sites/default/files/product-files/Effective_Teacher_Professional_Development_REPORT.pdf
• Matherson, L. H., Wilson, E. K., & Wright, V. H. (2014). Need TPACK? Embrace sustained professional development. Delta Kappa Gamma Bulletin, 81(1).
• Mollick, E. (2024) Co-Intelligence. Living and Working with AI. https://www.penguinrandomhouse.com/books/741805/co-intelligence-by-ethan-mollick/

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 teaching: Motivating Sustained Integrated Professional Development. International Journal for Computer Assisted Language Learning and Teaching https://www.igi-global.com/gateway/article/full-text-html/378304

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 Integrated Professional Development (SIPD). This is the second episode of the series and also the second discussion of the position paper on SIPD; episode 1 looked at the technical underpinnings of GenAI.

In this episode:

• Hubbard & Schulze (2025). AI and the future of language teaching: Motivating Sustained Integrated Professional Development. International Journal for Computer Assisted Language Learning and Teaching https://www.igi-global.com/gateway/article/full-text-html/378304
• UNESCO. (2024). AI competency framework for teachers. UNESCO Publishing. Available at https://unesdoc.unesco.org/ark:/48223/pf0000391104
• Educause Framework for AI literacy in teaching and learning (2024) https://www.educause.edu/content/2024/ai-literacy-in-teaching-and-learning/faculty-altl
• ISTE Whitepaper about evolving teacher education in an AI world: https://1818747.fs1.hubspotusercontent-na1.net/hubfs/1818747/2024_ISTE_whitepaper_EvolvingTeacher_Ed_in_an_AI_World.pdf
• Paradox Learning AI toolkit for educators: https://paradoxlearning.com/wp-content/uploads/2023/09/AI-Toolkit-for-Educators_v3.pdf
• Emily M. Bender & Alex Hanna (2025), The AI Con https://thecon.ai/

Additional reading:

Ohashi L. & Hubbard P. (2025). Generative AI ethics: Emerging principles for language teachers. In Ohashi L., Hills M., & Dykes R. (Eds.), Artificial intelligence in our language learning classrooms. Candlin & Mynard. https://www.candlinandmynard.com/uploads/1/2/5/0/12502105/chapter_5_open_access.pdf https://www.candlinandmynard.com/genai1.html

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.press/mat
• Emily Bender: https://faculty.washington.edu/ebender/
• Open-access position paper on Sustained Integrated Professional Development for GenAI (GenAI-SIPD): https://www.igi-global.com/gateway/article/378304