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Artificial intelligence in education: computer-assisted learning and AI-guided tutors

Author

Listed:
  • Sevilla Sanz, Maria Almudena
  • Cuevas Ruiz, Pilar
  • Rello, Luz
  • Sanz, Ismael

Abstract

Artificial Intelligence (AI) and Computer-Assisted Learning (CAL) offer powerful tools to improve foundational skills and close educational gaps, with evidence showing meaningful gains in student performance, especially in mathematics. Recent advancements in these technologies have generated optimism about their transformative potential in classrooms worldwide. These technologies are increasingly being piloted at scale, reshaping the way teachers deliver content and students engage with material. However, their impact depends less on access to devices and more on how they are integrated into teaching—through curriculum alignment, teacher training, and interactive design that promotes active learning. Without careful implementation, these tools risk widening existing inequalities. Using new evidence from Italy, we show that digital divides in AI adoption persist across schools and regions, reflecting broader social and economic disparities. Our findings suggest that realising the potential of AI in education requires inclusive policies and targeted investment to ensure no student is left behind, and that the benefits of digital innovation are shared equitably.

Suggested Citation

  • Sevilla Sanz, Maria Almudena & Cuevas Ruiz, Pilar & Rello, Luz & Sanz, Ismael, 2025. "Artificial intelligence in education: computer-assisted learning and AI-guided tutors," LSE Research Online Documents on Economics 130010, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:130010
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    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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