# Generative AI and Its Impact on Personalized Intelligent Tutoring Systems

arXiv: https://arxiv.org/abs/2410.10650 · HTML: https://mlsanity.com/paper/2410.10650/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 29 references that are in the map.
- First posted on arXiv 14 Oct 2024.

## Builds on (most cited first, 2 of 2)

- [Exploring the Capabilities of Prompted Large Language Models in Educational and Assessment Applications](https://mlsanity.com/paper/2405.11579/) (2024)
- [Intelligent Tutor: Leveraging ChatGPT and Microsoft Copilot Studio to Deliver a Generative AI Student Support and Feedback System within Teams](https://mlsanity.com/paper/2405.13024/) (2024)

## Built on by (most cited first, 11 of 11)

- [A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures](https://mlsanity.com/paper/2506.19676/) (2025)
- [Generative AI in Education: From Foundational Insights to the Socratic Playground for Learning](https://mlsanity.com/paper/2501.06682/) (2025)
- [Can LLMs Infer Personality from Real World Conversations?](https://mlsanity.com/paper/2507.14355/) (2025)
- [Prompt Engineering Using GPT for Word-Level Code-Mixed Language Identification in Low-Resource Dravidian Languages](https://mlsanity.com/paper/2411.04025/) (2024)
- [Agentic Persona Control and Task State Tracking for Realistic User Simulation in Interactive Scenarios](https://mlsanity.com/paper/2601.15290/) (2025)
- [Open TutorAI: An Open-source Platform for Personalized and Immersive Learning with Generative AI](https://mlsanity.com/paper/2602.07176/) (2026)
- [Cancer-Answer: Empowering Cancer Care with Advanced Large Language Models](https://mlsanity.com/paper/2411.06946/) (2024)
- [CryptoLLM: Unleashing the Power of Prompted LLMs for SmartQnA and Classification of Crypto Posts](https://mlsanity.com/paper/2411.07917/) (2024)
- [Evaluating the Impact of AI-Powered Audiovisual Personalization on Learner Emotion, Focus, and Learning Outcomes](https://mlsanity.com/paper/2505.03033/) (2025)
- [Human-AI collaboration or obedient and often clueless AI in instruct, serve, repeat dynamics?](https://mlsanity.com/paper/2508.10919/) (2025)
- [Enhancing knowledge tracing robustness for new question cold start in Intelligent Tutoring Systems](https://mlsanity.com/paper/2512.07179/) (2025)

## Abstract (arXiv)

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.