Language Teaching in the Age of Artificial Intelligence

October 2025

Artificial Intelligence, in the form of Large Language Models, are seemingly everywhere these days: embedded in our smartphones, our computers, our internet browsers, our search engines, and of course our classrooms. How then, can teachers best utilize these seemingly-ubiquitous tools to better help our students learn? This month, let’s take some time to ponder the implications of this new technology for teaching. 

“You cannot teach today the same way you did yesterday to prepare students for tomorrow.” – John Dewey

APA Reference for this issue

(author). (2025). (article title, sentence case). MindBrainEd Think Tanks: Language Teaching in the Age of Artificial Intelligence, 11(10), (pages).

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Back in March 2023, a few short months after ChatGPT was released, we took our first deep dive into artificial intelligence. In this issue, we revisit the intersection of artificial intelligence and language teaching and learning. In our Main video educators Laura Friday and Kevin Mount talk about how their opinions of AI have changed from feeling anxious about it to recognizing its potential uses. In our More podcast episode, Nik Peachey and Ann-Marie Murphy discuss specific ways generative AI can be used to support language learners and language teachers. And our Much More video emphasizes the importance of ensuring that different cultural perspectives are included in generative AI. Then, Nicky De Proost introduces the Think Tank.

In the Think Tank, Mirela C. C. Ramacciotti reflects on the complex interplay of teachers’ well-being, their perceptions of AI, and the ethical decisions they  need to make concerning AI. Then, Mark Brierley and Gary Ross examine the advances in large-language models and compare the ways AI is trained to the ways humans can learn languages through extensive reading. Next, Heather Kretschmer gives an overview of what language teachers need to consider before having learners use AI and then describes one strategy teachers can try out to encourage learners to retain ownership of their writing as they interact with AI. As a follow-up to her article, Heather Kretschmer briefly writes about a special app that combines writing and art. Finally, Afon (Mohammad) Khari discusses the impact of a recent MIT study on public perceptions of the effects of ChatGPT on the brain and reflects on the value of careful reading, effective science communication, and high-quality research.

Finally in our Plus, Mirela C. C. Ramacciotti summarizes the contributions Immanuel Kant, David Ausubel, Mark Bransford, and Marcia Johnson made to our understanding of the role of prior knowledge in learning.

Our Thoughts on AI & LLMs

An illustration of a cute robot and a bookshelf.

AI in Education: Friend, Foe, or Filing Clerk? Nicky De Proost

Imagine summoning a teaching assistant by snapping your fingers. That’s the dream, right? One moment you’re staring at a blank lesson plan, the next there’s someone beside you with a stack of worksheets ready to go. The magic trick is impressive—until they also start offering to write your end-of-term reports, mark your essays, and, disturbingly, draft your wedding vows.

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Think Tank Articles

A diagram summarizing teachers' perceptions of ethics and AI.

AI and Teachers’ Perceptions Mirela C. C. Ramacciotti

In this short article, I’ll give you a bird’s eye view of topics that have been receiving greater attention recently. Indeed, attention is necessary, for they may hold some pathways for weaving AI into busy teaching routines more seamlessly. The bird’s eye view is the following [above left]… 

In previous (Ramacciotti, in press) and present works (underway), I’ve been researching each of the topics [above left], amassing the breadcrumbs that a holistic perspective demands. The account of what I’ve been able to gather carries implications to how teachers adopt and use AI in the classroom…

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A diagram depicting the old "rules-based" model of early machine translators.

Has AI been doing ER? Mark Brierley & Gary Ross

When we look back and ask exactly when AI took over, we may pinpoint November 2022. That was when ChatGPT was launched and reached a million users within a week. Technically, the victory of DeepMind over LeeSedol may have been an earlier signal that the technology had come of age (watch: Krieg, 2017), but DeepMind’s’s victory was in the game of Go, which most people do not know. ChatGPT, on the other hand, was demonstrating a high level of proficiency in language, which is an area that most humans are expert in, and therefore able to judge and, perhaps more tellingly, criticise any shortcomings…

Read More
A classic painting of a young woman looking behind her at a cloudy sky.

Taking the AI Plunge: Thoughts about Using Artificial Intelligence to Support Language Learning Heather Kretschmer

Clutching precious books in her arms, a woman reaches the edge of the cliff and stops. As the howling gale whips back her hair and dress, the woman gazes resolutely at the dark, stormy landscape ahead. Her thoughts circle around like birds of prey ready to strike. Should she step off the precipice? Is what awaits her below worth the plunge into the unknown? Can she still hold on to her values in that potentially uncomfortable future?

Read More
A screen capture from the Curaturae website.

Curaturae: Combining Art and Text in Curious Ways Heather Kretschmer

You may have noticed the images in the article I wrote for this issue, “Taking the AI Plunge,” and wondered why I chose centuries-old artwork for an article about cutting-edge technology. Well, I drafted my article using this delightful app: https://curaturae.com/. The app connects language with art from the Smithsonian Open Access. So, as I typed in my sentences, art pieces appeared, a few of which are included in my article. I liked the parallels between beautiful art created by humans and beautiful writing from students.

Read More
A cute robot holding a book.

Clickbait Neuroscience: Lessons from “Your Brain on ChatGPT” Afon (Mohammad) Khari

Every few months, a study makes headlines with claims about how technology is reshaping our brains. The latest came from the MIT Media Lab, titled “Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task” (Kosmyna et al., 2025). Within hours of its release, LinkedIn and news outlets buzzed with takes like “ChatGPT makes you dumber.”

But here’s the catch: the authors never said that.

Read More

Think Tank Plus

A portrait of Immanuel Kant.

Great Ideas from the Brain Sciences: The Role of Prior Knowledge Mirela C. C. Ramacciotti

Have you ever wondered where students get some of their ideas? If it is from their own knowledge base, then how can we know more about it? And if we want to assess how much they know about a topic, what priors are we tapping into? If those are your questions when preparing a class or thinking about how to tackle a difficult topic, rest assured that you’re not alone. For centuries, great thinkers have posed—and dwelled upon—the same notion. Some ideas survived the test of time, and it is with one of them that we’ll begin our journey to understand the role of prior knowledge.

Read More

Call for Contributions: Ideas and Articles Think Tank Staff

Become a Think Tank star! Here are some of the future issue topics we are thinking about. Would you, or anyone you know, like to write about any of these? Or is there another topic you’d like to recommend? Do you have any suggestions for lead-in, or just plain interesting, videos? How about writing a book review? Or sending us a story about your experiences? Contact us.

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Going Deeper

Education Hazards of Generative AI

If you’ve ever wondered whether large-language models are clever new colleagues or just very confident parrots, this paper by Benjamin Riley and Paul Bruno has you covered. It peels back the hype to ask five deceptively simple questions:

  • What are large-language models designed to do?
  • Do they learn the way humans do?
  • Can they actually reason?
  • Does their existence make what we teach in schools obsolete?
  • And, the perennial favourite, will they outsmart us entirely?

Each question is answered with clarity, cutting through the sales patter and pointing out where the risks lie—bias baked into training data, the illusion of reasoning, the danger of outsourcing too much trust. It’s a bracing read, but a reassuring one too: these models may be overeager assistants, but they’re not about to run the school just yet.

If you’re curious (or worried) about what AI really can and can’t do, read the full paper here, and arm yourself with answers before the next “AI will take over education” headline lands.

The MindBrained Think Tanks+

is produced by the Japan Association for Language Teaching (JALT) Mind, Brain, and Education Special Interest Group (BRAIN SIG). Kyoto, Japan. (ISSN 2434-1002)

Editorial Staff

      Stephen M. Ryan               Curtis H. Kelly              Julia Daley     

 Afon (Mohammad) Khari     Heather Kretschmer     Nicky De Proost

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