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AI and personalized learning: bridging the gap with modern educational goals
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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 goals outlined in the OECD Learning Compass 2030. Our analysis indicates a gap between the objectives of modern education and the technological approach to PL. We identify areas where the AI-based PL solutions could embrace essential elements of contemporary education, such as fostering learner's agency, cognitive engagement, and general competencies. While the PL solutions that narrowly focus on domain-specific knowledge acquisition 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 generative AI, such as ChatGPT, and propose a hybrid model that blends artificial intelligence with a collaborative, teacher-facilitated approach to personalized learning.
Forward citations
Cited by 2 Pith papers
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TaleForge: Interactive Multimodal System for Personalized Story Creation
TaleForge generates stories and illustrations in which the user's face becomes the main character, using Llama3 plus diffusion models and a 12-person user study showing stronger engagement.
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MindCraft: Revolutionizing Education through AI-Powered Personalized Learning and Mentorship for Rural India
MindCraft is a conceptual AI education platform for rural India, but the paper provides no implementation, data, or evidence.
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