When I think about adult English language education in British Columbia in 2035, I see a future that is both promising and concerning. AI will likely provide increasingly sophisticated language instruction, allowing learners to practise grammar, vocabulary, pronunciation, and writing independently. However, I worry that learners may become too dependent on these tools. I already see students using AI to create polished resumes that do not reflect their actual English abilities, which can become a problem when they reach a job interview.
Selwyn (2024) argues that not everything meaningful in education can be statistically modelled because learning also involves relationships, judgement, emotion, context, and values. Similarly, Bozkurt et al. (2023) suggest that as AI takes over more routine instructional tasks, the role of educators may shift toward relationship-building, judgement, mentoring, and contextual support.
By 2035, financial pressures may encourage organizations to use AI to reduce costs, potentially resulting in fewer teaching positions. My hope is that human instructors will remain essential, particularly for adult newcomers who need more than language instruction. They also need help navigating Canadian workplaces, culture, communities, and everyday life. For me, the future is therefore neither entirely optimistic nor pessimistic: AI may change ESL teaching considerably, but it may also clarify what human educators uniquely contribute.
References
Bozkurt, A., Xiao, J., Lambert, S. R., Pazurek, A., Crompton, H., Koseoglu, S., Farrow, R., Bond, M., Nerantzi, C., Honeychurch, S., Bali, M., Dron, J., Mir, K., Stewart, B., Costello, E., Mason, J., Stracke, C. M., Romero-Hall, E., Koutropoulos, A., & Toquero, C. M. (2023). Speculative Futures on ChatGPT and Generative AI: a Collective Reflection from the Educational Landscape. Asian Journal of Distance Education, 18(1).
Selwyn, N. (2024). On the Limits of Artificial Intelligence (AI) in Education. Nordisk tidsskrift for pedagogikk og kritikk, 10, 3–14. https://doi.org/10.23865/ntpk.v10.6062
14 October 2026 at 9:50 pm
Hi Christina, I thought your take on the future of AI in the English classroom was interesting and I agree with you that the role of AI will provide significant complexities for student learning. In your post you comment on how AI could take routine tasks and humans handle the ‘relationship-building, judgement, mentoring, and contextual support’ but how will we know where the line is? How can we determine where an AI stops and people begin? The differences are important. I think the idea of having AI take over ‘instructional tasks’ is concerning because we don’t really know how the AI of the future will determine the best ‘instructions’ for students. How would the AI explain the emotions of the poem “Tyger Tyger, burning bright.” Perhaps the AI might just consider it Tiger Tiger? Or how can it determine which students’ stories are ‘more creative’. I think the idea of putting AI in an instructional role might be a monumental misstep.
16 October 2026 at 4:13 am
Thanks Vince! I think you raise a really important question about where we draw the line between AI and human instruction. I honestly don’t know if we will always know where that line is, especially as AI becomes more sophisticated.
I can already see some of the problems with this in my own teaching. Students can use AI to produce a very polished resume or cover letter, but sometimes the language does not reflect their actual English ability. The technology has completed the task, but has the student actually learned from it?
Your examples about poetry and creativity also make me think about how much teaching depends on interpretation, emotion, context, and knowing the individual learner. AI may become very good at explaining grammar, vocabulary, or even pronunciation, but I am much less convinced that it can replace the human judgement and interaction involved in teaching. Maybe the bigger question for 2035 is not what AI can teach, but what we should allow it to teach.
18 October 2026 at 3:08 pm
Hi Christina, you post brings up some really good points in that the future holds sophistication, but at the cost of dependency. I also experience the disconnect between meeting students in person and having a conversation with them vs. reading their written output. This causes me think about Deaf sign language and American Sign Language interpreter training which requires students to immerse themselves in the CULTURE to deepen their understanding of ASL. Learning does not just happen in one dimension, but multi-dimensional framework to gain holistic views, experiences, and understandings. Great closing! “Maybe the bigger question for 2035 is not what AI can teach, but what we should allow it to teach.”
19 October 2026 at 4:46 am
Thanks Tara! I really like your point about learning being multidimensional and the importance of culture. I see something similar with newcomers learning English. They can learn vocabulary and grammar, but so much of communication comes from interacting with people and understanding the culture and context around the language. I think that is one of the things AI will have a difficult time replacing.
On another note, since you mentioned ASL, I have always wanted to learn it and add it to my list of languages! I actually learned fingerspelling in high school with my best friend. We donated some money to a man who gave us an ASL alphabet card, and then learned the alphabet so we could communicate with each other during class instead of passing notes because we always got busted! I still remember all of it all these years later.
I remember we talked a little about ASL during our book club too. Is there somewhere you would recommend studying it? I would much rather ask you than just randomly pick an online course. I just thought of something else: I could have used this as evidence for this course! Emerging technology disrupts traditional classroom communication practices. Clark and Kozma could have debated whether the fingers were merely delivery vehicles! haha
20 October 2026 at 1:11 pm
Hi Christina,
It’s good to see our debate carrying on into Assignment 3. Your resume example is almost exactly what I saw with my software development students. Some could produce working code with AI without really understanding it, and that gap became obvious when they went for jobs. Some struggled to get through technical interviews, while others got hired but couldn’t make it through their three-month probation period.
Your newcomers and my graduates seem to face the same problem. AI can help them produce better work, but that doesn’t necessarily mean they’re developing the skills they’ll need on their own.
I agree that this shows how important human educators still are. But with the financial pressures you mention, I wonder how we can make good use of AI in teaching without leaving students dependent on it when they enter the workforce.
26 October 2026 at 7:52 am
Thanks Craig! I was thinking the same thing: apparently our debate isn’t quite over yet!
I think your software students and my newcomers really are facing the same issue. AI can help someone produce something that looks great, but eventually they have to demonstrate those skills themselves, whether that is in a technical interview, a job interview, or once they are actually on the job.
I think part of the answer may be teaching students how to use AI without always relying on it. We probably should not discourage them from using a tool that is going to be part of their working lives, but we also need to give them opportunities to practise without it. For my learners, that could mean using AI to help improve a resume, but then practising how to talk about their experience in their own words during a mock interview.
Maybe our role as educators is becoming less about keeping students away from AI and more about helping them recognize when it is helping them learn and when it is doing the learning for them.