AI and personalized learning: bridging the gap with modern educational goals (2404.02798v1)

Abstract: Personalized learning (PL) aspires to provide an alternative to the one-size-fits-all approach in education. Technology-based PL solutions have shown notable effectiveness in enhancing learning performance. However, their alignment with the broader goals of modern education is inconsistent across technologies and research areas. In this paper, we examine the characteristics of AI-driven PL solutions in light of the OECD Learning Compass 2030 goals. Our analysis indicates a gap between the objectives of modern education and the current direction of PL. We identify areas where most present-day PL technologies could better embrace essential elements of contemporary education, such as collaboration, cognitive engagement, and the development of general competencies. While the present PL solutions are instrumental in aiding learning processes, the PL envisioned by educational experts extends beyond simple technological tools and requires a holistic change in the educational system. Finally, we explore the potential of LLMs, such as ChatGPT, and propose a hybrid model that blends artificial intelligence with a collaborative, teacher-facilitated approach to personalized learning.