Technological, Pedagogical, and Sociocultural Impact Factors and Effective Implementation Strategies of Ai-Driven Personalized Learning for College Students
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บทคัดย่อ
With the rapid advancement of Artificial Intelligence (AI) technological advancements, its application in higher education continues to deepen, demonstrating significant potential particularly in the field of personalized learning. AI-Driven personalized learning achieves precise resource matching and dynamic feedback by analyzing students' learning behaviors and cognitive characteristics, thereby enhancing learning efficiency and experience. However, the application of AI in education still faces multiple challenges, including insufficient algorithm transparency, disparities in digital literacy between teachers and students, data privacy and security risks, and educational equity. Based on a comprehensive analysis of existing literature and practical cases, this study explores the impact mechanisms of AI-Driven personalized learning from three dimensions—technological factors, pedagogical factors, and sociocultural factors—to construct a theoretical research framework. The research aims to clarify the core influencing factors and pathways of AI-empowered personalized learning, propose corresponding educational practice strategies, and provide theoretical support and reference for the intelligent transformation and educational equity in higher education.
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บทความที่ปรากฏในวารสารนี้ เป็นความรับผิดชอบของผู้เขียน ซึ่งสมาคมนักวิจัยไม่จำเป็นต้องเห็นด้วยเสมอไป การนำเสนอผลงานวิจัยและบทความในวารสารนี้ไปเผยแพร่สามารถกระทำได้ โดยระบุแหล่งอ้างอิงจาก "วารสารสมาคมนักวิจัย"
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