# GPTutor: Great Personalized Tutor with Large Language Models for Personalized Learning Content Generation

arXiv: https://arxiv.org/abs/2407.09484 · HTML: https://mlsanity.com/paper/2407.09484/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 May 2024.

## Built on by (most cited first, 9 of 9)

- [From Recall to Forgetting: Benchmarking Long-Term Memory for Personalized Agents](https://mlsanity.com/paper/2604.20006/) (2026)
- [VTutor: An Animated Pedagogical Agent SDK that Provide Real Time Multi-Model Feedback](https://mlsanity.com/paper/2505.06676/) (2025)
- [When AI Agents Learn from Each Other: Insights from Emergent AI Agent Communities on OpenClaw for Human-AI Partnership in Education](https://mlsanity.com/paper/2603.16663/) (2026)
- [ALTO: Adaptive LoRA Tuning and Orchestration for Heterogeneous LoRA Training Workloads](https://mlsanity.com/paper/2604.05426/) (2026)
- [Evaluating Large Language Models for automatic analysis of teacher simulations](https://mlsanity.com/paper/2407.20360/) (2024)
- [Chat-Based Support Alone May Not Be Enough: Comparing Conversational and Embedded LLM Feedback for Mathematical Proof Learning](https://mlsanity.com/paper/2602.18807/) (2026)
- [Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Education](https://mlsanity.com/paper/2604.07253/) (2026)
- [Lect=uraAgents: A Multi-Agent Framework for Adaptive Personalized AI-Assisted Learning and Embodied Teaching](https://mlsanity.com/paper/2606.16428/) (2026)
- [A Prompt-Engineering Approach to Develop Scalable, Flexible, and Real-Time Hybrid Micro-Level Personalization in a General Purpose AI Teaching Assistant](https://mlsanity.com/paper/2609.03402/) (2026)

## Abstract (arXiv)

We developed GPTutor, a pioneering web application designed to revolutionize personalized learning by leveraging the capabilities of Generative AI at scale. GPTutor adapts educational content and practice exercises to align with individual students' interests and career goals, enhancing their engagement and understanding of critical academic concepts. The system uses a serverless architecture to deliver personalized and scalable learning experiences. By integrating advanced Chain-of-Thoughts prompting methods, GPTutor provides a personalized educational journey that not only addresses the unique interests of each student but also prepares them for future professional success. This demo paper presents the design, functionality, and potential of GPTutor to foster a more engaging and effective educational environment.