# Generative AI and Teachers -- For Us or Against Us? A Case Study

arXiv: https://arxiv.org/abs/2404.03486 · HTML: https://mlsanity.com/paper/2404.03486/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 64 references that are in the map.
- First posted on arXiv 4 Apr 2024.

## Builds on (most cited first, 5 of 5)

- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education](https://mlsanity.com/paper/2305.00290/) (2023)
- [The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and Millennial Generation teachers?](https://mlsanity.com/paper/2305.02878/) (2023)
- [Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code](https://mlsanity.com/paper/2404.00399/) (2024)
- [ProCoT: Stimulating Critical Thinking and Writing of Students through Engagement with Large Language Models (LLMs)](https://mlsanity.com/paper/2312.09801/) (2023)

## Built on by (most cited first, 6 of 6)

- [Fairness and Bias in Multimodal AI: A Survey](https://mlsanity.com/paper/2406.19097/) (2024)
- [On the Limitations of Large Language Models (LLMs): False Attribution](https://mlsanity.com/paper/2404.04631/) (2024)
- [Findings of MEGA: Maths Explanation with LLMs using the Socratic Method for Active Learning](https://mlsanity.com/paper/2507.12079/) (2025)
- [AI Must not be Fully Autonomous](https://mlsanity.com/paper/2507.23330/) (2025)
- [In Generative AI We (Dis)Trust? Computational Analysis of Trust and Distrust in Reddit Discussions](https://mlsanity.com/paper/2510.16173/) (2025)
- [From the Rock Floor to the Cloud: A Systematic Survey of State-of-the-Art NLP in Battery Life Cycle](https://mlsanity.com/paper/2510.27369/) (2025)

## Abstract (arXiv)

We present insightful results of a survey on the adoption of generative artificial intelligence (GenAI) by university teachers in their teaching activities. The transformation of education by GenAI, particularly large language models (LLMs), has been presenting both opportunities and challenges, including cheating by students. We prepared the online survey according to best practices and the questions were created by the authors, who have pedagogy experience. The survey contained 12 questions and a pilot study was first conducted. The survey was then sent to all teachers in multiple departments across different campuses of the university of interest in Sweden: Luleaa University of Technology. The survey was available in both Swedish and English. The results show that 35 teachers (more than half) use GenAI out of 67 respondents. Preparation is the teaching activity with the most frequency that GenAI is used for and ChatGPT is the most commonly used GenAI. 59% say it has impacted their teaching, however, 55% say there should be legislation around the use of GenAI, especially as inaccuracies and cheating are the biggest concerns.