The “TOP” drivers of academics’ adoption of ChatGPT in teaching
Bibliographic Data
| ID | 8246137 |
|---|---|
| Authors | Mohamed Yacine Haddoud (0000-0002-2335-2389), Witold Nowiński (0000-0002-3694-8317), Ahmed Bawa Kuyini (0000-0003-1083-8862), Julien Issa (0000-0002-6498-7989), Marta Dyszkiewicz-Konwińska (0000-0002-8069-9004) |
| Year | 2025 |
| Pages | 1-22 |
| Publication date | 2025-12-17 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Information Communication and Ethics in Society (JOURNAL) |
| Journal identifiers | ISSN: 1758-8871 • E-ISSN: 1477-996X |
| Publisher | Emerald (PUBLISHER) |
| DOI | 10.1108/jices-10-2025-0282 |
| OpenAlex | W4417415445 |
| Language | EN |
| References cited | 66 |
Purpose The purpose of this research is to investigate the factors that affect educators’ adoption of ChatGPT for teaching activities. Design/methodology/approach Using the TOP framework, this research uses a survey methodology, gathering data from 479 higher education staff across various universities and countries. Findings This study reveals that performance expectancy, effort expectancy, artificial intelligence (AI) learning and anxiety indirectly affect the adoption of ChatGPT by enhancing attitudes and self-efficacy. Notably, AI exposure and perceived support do not have a significant impact. Overall, the model accounts for 55% of the variance in ChatGPT adoption intentions. Practical implications The findings suggest that technology and personnel-related factors can improve the adoption of ChatGPT for teaching, while organisational factors are less influential. This has important implications for educational institutions considering the integration of AI tools. Originality/value This research contributes to the limited literature on educators’ use of ChatGPT in teaching, providing insights into the underlying factors that facilitate or hinder its adoption in the educational landscape
Affect (linguistics · Data collection · Higher education · Information technology · Survey data collection · Survey research · Technology Acceptance Model · Variance (accounting · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · E-Learning and COVID-19
The Roles of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes toward Artificial Intelligence
Mails - Meta AI literacy scale
ChatGPT in education
Educational Technology Adoption
The theory of planned behavior
The theory of planned behaviour
User Acceptance of Information Technology
When to use and how to report the results of PLS-SEM
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
A Theoretical Extension of the Technology Acceptance Model
Validation of a New General Self-Efficacy Scale
What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature
Development and Evaluation of a Custom GPT for the Assessment of Students’ Designs in a Typography Course
ChatGPT—A Challenging Tool for the University Professors in Their Teaching Practice
The opportunities and challenges of ChatGPT in education
Adoption of artificial intelligence (AI) based employee experience (EEX) chatbots
ChatGPT in the higher education
Human confidence in artificial intelligence and in themselves
Technology acceptance theories and factors influencing artificial Intelligence-based intelligent products
Understanding academics' adoption of learning technologies
The critical determinants impacting artificial intelligence adoption at the organizational level
An investigation of mobile learning readiness in higher education based on the theory of planned behavior
Bringing academics on board
Hallucinations in ChatGPT
Inclusive education
Why do people use information kiosks? A validation of the Unified Theory of Acceptance and Use of Technology
Comprehension, apprehension, and acceptance
Drivers of generative AI adoption in higher education through the lens of the Theory of Planned Behaviour
Use of ChatGPT in academia
| Citation velocity | historical |
|---|---|
| Highly cited | No |