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5 Things Every Language Teacher Should Know About AI




There is a mix of excitement and concern about the implications of artificial intelligence and big data for English language teaching. In our new Talking ELT podcast, Professor Hayo Reinders and Ben Knight sat down to discuss the pros and cons of AI, big data and other emerging technologies. Like with most complex issues, there are no simple answers. But here are five key areas for teachers to reflect on.

1. English Teachers are still needed in a world with AI

AI will be able to create mountains of individualized, valuable, interactive content. However, teachers will still be needed to provide a human touch. We need what has been called a ‘human-in-the-loop’ (HITL) to ensure the use of AI is based on our values as teachers and represents the interests of our learners and communities. What this means is that our roles are likely to shift further away from content providers to being mediators of learning. AI is likely to free us from some of the time-consuming and repetitive aspects of our work, such as creating exercises and checking homework. This will give us the opportunity to guide our students through the learning process and provide personal feedback and support. These are the types of work most of us enjoy, are really good at, and are unlikely to be replaced by new technologies.

2. Artificial Intelligence will change Materials development

AI will make our lives easier in many ways. But we need experienced teachers to ensure that the materials that AI produces are suitable, appropriate and in the best interests of our learners. For generative AI to be most beneficial, specialized knowledge and expertise are vital. And it is precisely our pedagogical knowledge and our personal relationships with learners that are needed for this. AI can help teachers create individualized materials for students. But it is up to teachers to turn these materials into engaging, relevant, and effective learning experiences.

3. Artificial intelligence will transform Learner assessment

Using AI to interpret educational data will provide a much more complete view of the learner that no longer limits us to summing their learning up in a single score. Using learning analytics (for example through the various ‘dashboards’ that learning management systems as well as individual apps and websites provide) we can gain insights into what learners do, what they struggle with and how they regulate their learning. What this means is that we can gain insight into the learning process, not simply the outcome. And we can do so in near real-time. This makes it possible to provide truly formative feedback. This will in most cases require a considerable change to current assessment methods to make the most of these new opportunities.

4. There are dangers if no one is in control of AI

Big data carries many risks, not least of all a loss of control on the part of teachers and learners. As we discussed in the podcast, instead of being blindly guided by algorithms without human supervision or intervention, ‘we need to become the algorithm’. Experts in our field (i.e. teachers, materials designers, curriculum developers, and so on) need to shape how AI is built, rather than leaving this exclusively to engineers. This means it is vital for teachers to become involved in the design, development, implementation, and evaluation of new technologies.

5. AI can complement traditional learning methods

AI can be a powerful tool for language learners. It can provide personalised instruction and feedback, adapt to individual learning preferences, and offer learning opportunities outside the classroom. This does come with a number of challenges. For example, how will we be able to monitor what learners do in their own time? And if learners receive personalised instruction, then how can we ensure everyone still benefits from the activities that take place in class? In some cases, such changes may prompt changes in how learners are grouped, supported, assessed, and more. We may have to consider more individualised pathways in which learners can be guided throughout the school curriculum, while still receiving the social support and continuity needed.


In summary, emerging technologies like artificial intelligence are not simply beneficial or detrimental. We are only just now starting to explore their possibilities and implications. It is only through considered experimentation on the part of teachers that we can gain the real-world insights necessary to move our field forward in a way that reflects our values and that serves our learners’ best interests. Find out more about the impact of AI on education and learn how you can make a difference in the first series of our new Talking ELT podcast.

Listen now!

Hayo Reinders (www.innovationinteaching.org) is TESOL Professor and Director of Research at Anaheim University, USA, and Professor of Applied Linguistics at KMUTT in Thailand. He is founder of the global Institute for Teacher Leadership and editor of Innovation in Language Learning and Teaching. His interests are in out-of-class learning, technology, and language teacher leadership. Hayo is the author of this paper.

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