Generative AI and Its Impact on Personalized Intelligent Tutoring Systems

Fuente: arXiv
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Main Authors: Maity, Subhankar, Deroy, Aniket
Format: Preprint
Published: 2024
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author Maity, Subhankar
Deroy, Aniket
author_facet Maity, Subhankar
Deroy, Aniket
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2410_10650
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Generative AI and Its Impact on Personalized Intelligent Tutoring Systems
Maity, Subhankar
Deroy, Aniket
Computation and Language
Artificial Intelligence
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.
title Generative AI and Its Impact on Personalized Intelligent Tutoring Systems
topic Computation and Language
Artificial Intelligence
url https://arxiv.org/abs/2410.10650