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What has changed in the past five years?
In 2019, we saw the first applications based on deep learning – think of image recognition and text applications, such as translation. “It was already clear at that time that this would bring many opportunities but also have an impact on education.”, says Tommy. The topic of 'AI in education' has since become even more relevant. A follow-up paper published by Nick and Tommy shortly after the research, was initially hardly noticed but has been cited dozens of times in the past year. “AI in education is receiving attention from all sides, including fortunately a lot of research interest,” says Tommy. In his current role, Nick utilises language models for research and teaching at the university.
One of the conclusions back then was that 'artificial general intelligence', or AI that is as intelligent or even smarter than humans, was still a thing of the future. “That is still the case, but with the introduction of ChatGPT something fundamental has changed: AI is no longer an abstract mathematical model, but 'feels' like a person you can talk to, ask questions.”, Tommy continues.
Did the research underestimate the development of AI at the time?
“In my opinion, with the knowledge we had back then, we made some very good predictions,” says Nick. “We correctly anticipated that AI would continue to develop significantly, however, predicting the specific direction it has taken now was impossible at that time,” Tommy adds. “The idea that something like a ‘large language model’, essentially an extremely large version of ‘autocomplete’, could work for generic tasks, that was truly surprising. In 2019, with chatbots, you were still thinking of 'closed’ systems – more like a customer service menu where you could interact, but with limited options. The language models break that mold.”
AI tools are very disruptive for teachers. They need to find new ways to assess their students' knowledge and skills.
Another aspect that was underestimated in 2019 is the impact of generative AI – students can have large parts of their assignments generated by the computer. Nick: “AI tools are very disruptive for teachers. They need to find new ways to assess their knowledge and skills of their students. Instead of essays, more emphasis is placed on, for example, oral presentations, where teachers can delve deeper with questions.”
Is the discussion on AI risks in education different than five years ago?
In the 2019 research, it was noted that an AI – just like a human teacher for that matter – is not neutral in values. This may not be a problem, as long as you know which values are at play, and that they align with the values the school stands for. The societal debate on AI in education closely relates to the broader discussion on AI deployment. “Regarding the language models, we see a lot of discussion, also beyond the education context, for example, around what materials have been used to develop the language model, who owns it, and what influence that has. It's great that this is being scrutinised. It starts with the language itself – a model like ChatGPT is very proficient in English, but works less efficiently in Dutch. It's no wonder that efforts are being made to develop a fully Dutch version.” says Tommy. Nick thinks it would be a good idea to focus more on value judgements: “The manufacturer determines the values in the final training step of the AI” – these values should be a key factor in selecting AI applications, but it's highly questionable if they are transparent.
Are schools and teachers now more conscious about AI? “I can't say for sure – during our research visits to schools, we observed significant differences. A school only needs one enthusiastic teacher to be at the forefront.” In the scientific literature, attention is now paid to the relationship between teachers and AI (e.g. Molenaar, 2022). Organisations like SURF are also engaged in the topic.
What does the next five years look like for AI in education?
“The previous research teaches us that it is very challenging to make specific predictions about how the implementation will be. However, I believe that the conclusions from back then still hold true. I hope that AI fulfils the promise of hyper-personalised education, without the negative impact it could have. It's reassuring to see that this is being carefully considered.” says Tommy. Nick, on the other hand, is actively involved in AI in education: “we are working on a language model that we can ultimately use to provide information to (future) students about the educational offerings at our university”.
As innovation scientists, both closely follow the subject. “Adoption of new, disruptive technologies in society is always fascinating. My high school was recently in the news because they were one of the first to completely ban mobile phones in class. I found that interesting because when I was in school there twenty years ago, it was the norm. The school allowed mobile phones after that and now has banned them again. We must continuously evaluate innovations”.
