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Generative AI and Its Impact on Personalized Intelligent Tutoring Systems

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arxiv 2410.10650 v1 pith:4GCYCTZ7 submitted 2024-10-14 cs.CL cs.AI

classification cs.CLcs.AI
keywords generativesystemspersonalizedreporttutoringadaptiveeducationeducational
verification ladder T0 review T1 audit T2 compute T3 formal
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Generative Artificial Intelligence (AI) is revolutionizing educational technology by enabling highly personalized and adaptive learning environments within Intelligent Tutoring Systems (ITS). This report delves into the integration of Generative AI, particularly large language models (LLMs) like GPT-4, into ITS to enhance personalized education through dynamic content generation, real-time feedback, and adaptive learning pathways. We explore key applications such as automated question generation, customized feedback mechanisms, and interactive dialogue systems that respond to individual learner needs. The report also addresses significant challenges, including ensuring pedagogical accuracy, mitigating inherent biases in AI models, and maintaining learner engagement. Future directions highlight the potential advancements in multimodal AI integration, emotional intelligence in tutoring systems, and the ethical implications of AI-driven education. By synthesizing current research and practical implementations, this report underscores the transformative potential of Generative AI in creating more effective, equitable, and engaging educational experiences.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Can LLMs Infer Personality from Real World Conversations?

    cs.CL 2025-07 conditional novelty 6.0 of 10

    LLMs predict personality from interview text with high internal consistency but weak construct validity (max r = 0.27, Cohen's kappa < 0.10) against BFI-10 self-reports.

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