The DOI matches its Crossref record, with a small difference in title or year; 13 of the 13 references it cites were found in a registry or an index.
Generative AI in Education: A Study of Educators' Awareness, Sentiments, and Influencing Factors
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This research full paper delves into university in-structors' 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 rapid advancement of artificial intelligence (AI) and the expanding integration of large language models (LLMs) have ignited a debate about their application in education. The objective of this research is to investigate the level of awareness, overall sentiment towards adoption, 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.
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Other U.S.-based studies reported higher overall rates of GenAI use than this study.
“other U.S.-based studies [6, 46] reported higher overall rates of GenAI use”
From Understanding the Practices, Perceptions, and (Dis)Trust of Generative AI among Instructors: A Mixed-methods Study in the U.S. Higher Education (2025) · cites this paper as [46]
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Cites
Artificial intelligence in education: Addressing ethical challenges in K-12 settings
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The Robots Are Here: Navigating the Generative AI Revolution in Computing Education
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“Recent advances in generative AI and natural language processing have enabled the development of large language models (LLMs) that show impressive capabilities in generating and reasoning about code [4].”
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Cited by
Sorted by citations
Graph Retrieval-Augmented Generation: A Survey
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Analyzing the Impact of AI Tools on Student Study Habits and Academic Performance
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Metadata
- Authors
- Ghimire, A., Pather, J., & Edwards, J.
- Affiliations
- Utah State University (US)
- Abilene Christian University (US)
- ORCID
- Edwards, John
- Venue
- 2024 IEEE Frontiers in Education Conference (FIE)
- Publisher
- IEEE
- Published
- 2024-10-13
- Pages
- 1-9
- ISSN
- 0190-5848 (ISSN-L)
- OpenAlex
- W4407951611
- Cited by
- 88
- References
- 13
- Citations by year
- 2026: 30 · 2025: 48 · 2024: 10
- FWCI
- 33.51
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- IEEE Frontiers in Education Conference (FIE) (publishedVersion)
- arXiv (Cornell University) (submittedVersion, cc-by-nc-sa)
- arXiv (Cornell University)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Education › Educational Technology and Pedagogy
- Keywords
- generative AI in education, large language models, university instructors, educator attitudes, AI awareness, teaching styles, AI-generated content detection, higher education
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