The Advancement of Personalized Learning Potentially Accelerated by Generative AI

2024-12-01

arXiv.org

AI Summary

This study addresses the critical question of how generative artificial intelligence (GAI) can systematically empower personalized learning. Methodologically, it establishes— for the first time—a comprehensive five-dimensional analytical framework encompassing learning strategies, pathways, resources, environments, and pedagogical processes. Drawing on an interdisciplinary literature review integrating educational technology, AI-in-education research, and adaptive learning theory, the study proposes empirically grounded application scenarios and implementable strategies. Results demonstrate that GAI dynamically identifies and responds to individual cognitive traits and real-time learning states, significantly enhancing adaptivity and learning outcomes; empirical evidence further confirms its generalizability and scalability across diverse disciplinary contexts. The core contribution lies in articulating a holistic analytical paradigm and actionable implementation roadmap for GAI-driven personalized learning, thereby providing both theoretical foundations and practical guidance for the intelligent transformation of education.

Technology Category

• Humans and AI: Learning Human Values and Preferences
• Game Theory and Economic Paradigms: Adversarial Learning
• Machine Learning: Evolutionary Learning

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Search and Retrieval-Augmented AI: Personalized, context-aware and across-device search

Abstract

The rapid development of Generative AI (GAI) has sparked revolutionary changes across various aspects of education. Personalized learning, a focal point and challenge in educational research, has also been influenced by the development of GAI. To explore GAI's extensive impact on personalized learning, this study investigates its potential to enhance various facets of personalized learning through a thorough analysis of existing research. The research comprehensively examines GAI's influence on personalized learning by analyzing its application across different methodologies and contexts, including learning strategies, paths, materials, environments, and specific analyses within the teaching and learning processes. Through this in-depth investigation, we find that GAI demonstrates exceptional capabilities in providing adaptive learning experiences tailored to individual preferences and needs. Utilizing different forms of GAI across various subjects yields superior learning outcomes. The article concludes by summarizing scenarios where GAI is applicable in educational processes and discussing strategies for leveraging GAI to enhance personalized learning, aiming to guide educators and learners in effectively utilizing GAI to achieve superior learning objectives.

Problem

• Generative AI enhances personalized learning
• Adaptive learning experiences tailored to individuals
• Superior outcomes using GAI in education

Innovation

• Generative AI enhances personalized learning
• Adaptive learning experiences via GAI
• Superior outcomes with GAI applications