Higher Education Faculty Perceptions of ChatGPT and the Influencing Factors
A Sentiment Analysis of X
Bibliographic Data
| ID | 12817433 |
|---|---|
| Authors | Yoseph Mamo (0000-0001-5171-5186, Old Dominion University, corresponding author), Helen Crompton (0000-0002-1775-8219, Old Dominion University), Diane Burke (0000-0002-8214-0386, Old Dominion University), Christine E Nickel (0009-0009-6420-3716, Old Dominion University) |
| Year | 2024 |
| Volume | 68 |
| Issue | 3 |
| Pages | 520-534 |
| Publication date | 2024-04-13 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | TechTrends (JOURNAL) |
| Journal identifiers | ISSN: 8756-3894 • E-ISSN: 1559-7075 |
| Publisher | Springer Science+Business Media (PUBLISHER • DE) |
| DOI | 10.1007/s11528-024-00954-1 |
| OpenAlex | W4394784173 |
| Language | EN |
| Citations received | 12 |
| References cited | 53 |
ChatGPT, an AI chatbot developed by OpenAI, was released in November 2022, sparking a significant surge in global awareness and utilization of generative AI across various domains. Although recent studies have acknowledged the significance of ChatGPT in the education sector, they have yet to focus on exploring faculty attitudes toward ChatGPT. We gathered a comprehensive corpus of tweets containing “#ChatGPT” and “#highered” between November 30th, 2022, and April 30th, 2023. We analyzed data by triangulating VADER, NRC lexicon, and ground coding. Findings suggest that 40% of the expressed sentiments were positive, 51% were neutral, and 9% were negative. The study also revealed the diverse range of emotions held by higher education faculty regarding ChatGPT, with trust and joy being the most prevalent positive sentiments and fear and anger being the most prevalent negative sentiments. This study shed light on faculty members’ perceptions of ChatGPT, contributing to a better understanding of the impact, emotions, and incorporation of ChatGPT in the higher education sector
Anger · Higher education · Lexicon · Linguistics · Perception · Political science · Artificial Intelligence in Healthcare and Education · Mental Health via Writing · Psychology · Social Psychology · Topic Modeling
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| Unique citing works | 12 |
|---|---|
| Citations per year | 6 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 12 |