mlsanityData to 7 Oct 2026

Generative AI in Education: A Study of Educators' Awareness, Sentiments, and Influencing Factors

arXiv 2403.15586 ↗First posted 22 Mar 2024cs.AIcited by 10

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Abstract (arXiv)

The rapid advancement of artificial intelligence (AI) and the expanding integration of large language models (LLMs) have ignited a debate about their application in education. This study delves into university instructors' experiences and attitudes toward AI language models, filling a gap in the literature by analyzing educators' perspectives on AI's role in the classroom and its potential impacts on teaching and learning. The objective of this research is to investigate the level of awareness, overall sentiment towardsadoption, and the factors influencing these attitudes for LLMs and generative AI-based tools in higher education. Data was collected through a survey using a Likert scale, which was complemented by follow-up interviews to gain a more nuanced understanding of the instructors' viewpoints. The collected data was processed using statistical and thematic analysis techniques. Our findings reveal that educators are increasingly aware of and generally positive towards these tools. We find no correlation between teaching style and attitude toward generative AI. Finally, while CS educators show far more confidence in their technical understanding of generative AI tools and more positivity towards them than educators in other fields, they show no more confidence in their ability to detect AI-generated work.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 14 of its 45 references that are in the map. First posted on arXiv 22 Mar 2024.

Builds on

14 of 45 references.

References · 14

  1. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  2. 2022Automatic Generation of Programming Exercises and Code Explanations using Large Language Modelscited by 124
  3. 2022Programming Is Hard -- Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code Generationcited by 97
  4. 2023The Robots are Here: Navigating the Generative AI Revolution in Computing Educationcited by 85
  5. 2022Experiences from Using Code Explanations Generated by Large Language Models in a Web Software Development E-Bookcited by 84
  6. 2022Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Languagecited by 81
  7. 2022Using Large Language Models to Enhance Programming Error Messagescited by 67
  8. 2023"It's Weird That it Knows What I Want": Usability and Interactions with Copilot for Novice Programmerscited by 62
  9. 2023Computing Education in the Era of Generative AIcited by 50
  10. 2023Large Language Models (GPT) Struggle to Answer Multiple-Choice Questions about Codecited by 31
  11. 2023Prompt Problems: A New Programming Exercise for the Generative AI Eracited by 31
  12. 2022AI-driven Development Is Here: Should You Worry?cited by 15
2 more
  1. 2022Robosourcing Educational Resources -- Leveraging Large Language Models for Learnersourcingcited by 9
  2. 2023A Case Study in Engineering a Conversational Programming Assistant's Personacited by 6

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Citing papers per year: 2024: 5; 2025: 5.

10 papers.