# Future-proofing Education: A Prototype for Simulating Oral Examinations Using Large Language Models

arXiv: https://arxiv.org/abs/2401.06160 · HTML: https://mlsanity.com/paper/2401.06160/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 12 references that are in the map.
- First posted on arXiv 22 Dec 2023.

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

- [A Comprehensive Overview of Large Language Models](https://mlsanity.com/paper/2307.06435/) (2023)
- [On the application of Large Language Models for language teaching and assessment technology](https://mlsanity.com/paper/2307.08393/) (2023)

## Built on by (most cited first, 1 of 1)

- [INSIGHT: Bridging the Student-Teacher Gap in Times of Large Language Models](https://mlsanity.com/paper/2504.17677/) (2025)

## Abstract (arXiv)

This study explores the impact of Large Language Models (LLMs) in higher education, focusing on an automated oral examination simulation using a prototype. The design considerations of the prototype are described, and the system is evaluated with a select group of educators and students. Technical and pedagogical observations are discussed. The prototype proved to be effective in simulating oral exams, providing personalized feedback, and streamlining educators' workloads. The promising results of the prototype show the potential for LLMs in democratizing education, inclusion of diverse student populations, and improvement of teaching quality and efficiency.