Can AI Transform Education to Ensure All Students Benefit?

I remember the day I first experienced artificial intelligence (AI) in education. It was the late ’90s, and I was a maths teacher at a school in London described as having “challenging circumstances.”

I looked at my students, eyes glued to their computer screens, ears covered by headphones, all working in silence using an adaptive maths program. While marvelling at the rare moment of tranquillity, I also wondered: If the students were learning from the technology, what was the point of me being there? After all, I was a teacher, and a rather good one (if I do say so myself!).

Using the student learning outcomes data generated by the educational technology (edtech) program, I split the class into two groups based on their competencies: I taught half of them, while the others worked quietly on their computers, and then we switched. I kept using the data generated by the program to inform my teaching, and over time the students’ results improved. Technology in service of the teacher and the students contributed to our maths results being a top 2% value-add in England!

Fast-forward to today: Generative AI technology is mind-blowing, with great potential to be harnessed for teaching and learning. In a world where seven out of 10 children born in a low- and middle-income countries cannot read by age 10, AI could help address the dramatic learning equity gaps. But this work needs careful thought.

I have experienced many edtech pitches over the years, but only a few have impressed me. Most are either too focused on the technology or on reaching large numbers of students, without considering the pedagogy, or they fail to address the challenges and barriers that underserved students face in accessing and using technology, particularly in low- and middle-income contexts.

Furthermore, it is all too rare to see any evidence of impact on learning outcomes. (If you don’t show impact, I will assume there is none!)

A few edtech solutions combine evidence and the best of human expertise and wisdom with the benefits that technology can afford, particularly in data analysis. And with the recent advances in AI, especially in natural language processing, speech recognition, and computer vision, I have seen pitches that have blown me away—they genuinely make me wish I were teaching again.

Here are three problems that students and teachers across the globe face, along with AI-based solutions that could help, if they are implemented with careful thought, informed by data, and focused on equity:

For a glossary of technical terms. See below.

Problem 1: Many students don’t have access to high-quality learning resources that are tailored to their needs, interests, and learning levels.

Students may struggle to learn from their starting point and at their own pace, receive timely and constructive feedback, or struggle to find motivation and support for their learning goals. If they fall behind, they are likely to stay behind and drop out, failing to acquire important life skills.