# Revolutionising Distance Learning: A Comparative Study of Learning Progress with AI-Driven Tutoring

arXiv: https://arxiv.org/abs/2403.14642 · HTML: https://mlsanity.com/paper/2403.14642/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 7 references that are in the map.
- First posted on arXiv 21 Feb 2024.

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

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [Large Language Models for Education: Grading Open-Ended Questions Using ChatGPT](https://mlsanity.com/paper/2307.16696/) (2023)

## Built on by (most cited first, 3 of 3)

- [A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures](https://mlsanity.com/paper/2506.19676/) (2025)
- [Personalized Knowledge Transfer Through Generative AI: Contextualizing Learning to Individual Career Goals](https://mlsanity.com/paper/2508.04070/) (2025)
- [Using AI-based Learning Assistants in Higher Education: A Large-Scale Descriptive Analysis](https://mlsanity.com/paper/2607.08748/) (2026)

## Abstract (arXiv)

Generative AI is expected to have a vast, positive impact on education; however, at present, this potential has not yet been demonstrated at scale at university level. In this study, we present first evidence that generative AI can increase the speed of learning substantially in university students. We tested whether using the AI-powered teaching assistant Syntea affected the speed of learning of hundreds of distance learning students across more than 40 courses at the IU International University of Applied Sciences. Our analysis suggests that using Syntea reduced their study time substantially--by about 27% on average--in the third month after the release of Syntea. Taken together, the magnitude of the effect and the scalability of the approach implicate generative AI as a key lever to significantly improve and accelerate learning by personalisation.