AI and personalized learning: bridging the gap with modern educational goals
arxiv(2024)
摘要
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 large language models, such as
ChatGPT, and propose a hybrid model that blends artificial intelligence with a
collaborative, teacher-facilitated approach to personalized learning.
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