Opening AI for Language Learning

PODCAST · education

Opening AI for Language Learning

Aimed at language educators seeking clarity, practical insights, and critical reflections in the rapidly changing AI landscape, the Opening AI for Language Learning (OAILL) podcast explores the evolving intersection of linguistics, pedagogy, and AI in language teaching and learning. Initiated by the Language and Applied Research Center at San Diego State University (SDSU-LARC), it features hosts Mat Schulze, Professor of German and Director of SDSU-LARC, and Phil Hubbard, Senior Lecturer Emeritus at the Stanford University Language Center, longtime colleagues with decades of experience in technology for language education. In place of the all-too-common hype surrounding AI, they offer conversations in which they and occasional guests share their research and practice-informed perspectives, commentaries on others’ work, and their own professional and personal AI experiences.We are grateful for the support for Opening AI for Language Learning by the Language and Applie

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    Welcome to Sustained Integrated Professional Development

    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.pdfMatherson, 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/

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    GenAI Stuff you need to know now (part 2)

    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

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    GenAI stuff you need to know now (part 1)

    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/378304UNESCO. (2024). AI competency framework for teachers. UNESCO Publishing. Available at https://unesdoc.unesco.org/ark:/48223/pf0000391104Educause 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

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    What the LLM?

    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/matEmily 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

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ABOUT THIS SHOW

Aimed at language educators seeking clarity, practical insights, and critical reflections in the rapidly changing AI landscape, the Opening AI for Language Learning (OAILL) podcast explores the evolving intersection of linguistics, pedagogy, and AI in language teaching and learning. Initiated by the Language and Applied Research Center at San Diego State University (SDSU-LARC), it features hosts Mat Schulze, Professor of German and Director of SDSU-LARC, and Phil Hubbard, Senior Lecturer Emeritus at the Stanford University Language Center, longtime colleagues with decades of experience in technology for language education. In place of the all-too-common hype surrounding AI, they offer conversations in which they and occasional guests share their research and practice-informed perspectives, commentaries on others’ work, and their own professional and personal AI experiences.We are grateful for the support for Opening AI for Language Learning by the Language and Applie

HOSTED BY

Mathias Schulze, Philip Hubbard

CATEGORIES

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