The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
Acceptance of Artificial Intelligence Application in the Post-Covid Era and Its Impact on Faculty Members’ Occupational Well-being and Teaching Self Efficacy: A Path Analysis Using the UTAUT 2 Model
Open accessAbstract
The purpose of the present study was to assess acceptance of Artificial Intelligence Application in the Post-covid Era and its impact of faculty members’ occupational well-being and teaching self efficacy using The UTAUT 2 Model. This study used a quantitative, non-experimental survey design to answer the research questions and study the relationships between the independent variables of performance expectancy, effort expectancy, social faculty members’ occupational well-being and teaching self efficacy. Faculty members from Umm AL-Qura University were targeted. An online questionnaire was used to collect data via Facebook and WhatsApp groups. I received a total of 350 questionnaire responses. They were 200 males(57.1%), and 150 females(42.9%). In confirmation of the research results, there is a significant positive relationship (p < .001) between occupational well-being (OWB)and teaching self efficacy(TSE) and performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), price value (PV), and habit (HB), indicating that faculty members are influenced by the constructs established in the UTAUT2 model in the adoption of AI.
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“The study on 350 Saudi Arabian faculty members found a significant positive relationship between the constructs of the updated unified theory of acceptance and use of technology.”
From A systematic literature review of attitudes, intentions and behaviours of teaching academics pertaining to AI and generative AI (GenAI) in higher education: An analysis of GenAI adoption using the UTAUT framework (2024) · cites this paper as Alhwaiti et al., 2023
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“All three studies found a significant positive relationship between the constructs of UTAUT and AI adoption.”
In the citing paper
“Three AI studies (Ahmad et al., 2023; Alhwaiti, 2023; Al-Riyami et al., 2023) invoked the UTAUT framework developed by Venkatesh et al. (2003).”
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“Alhwaiti et al. (2023) used the updated UTAUT2 model, which also explores hedonic motivation, price value and habit.”
From A systematic literature review of attitudes, intentions and behaviours of teaching academics pertaining to AI and generative AI (GenAI) in higher education: An analysis of GenAI adoption using the UTAUT framework (2024) · cites this paper as Alhwaiti et al., 2023
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User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
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Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709
Self-efficacy mechanism in human agency
Bandura, A. (1982) · American Psychologist · doi:10.1037/0003-066x.37.2.122 · Cited by 15,975
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756
Understanding digital transformation: A review and a research agenda
Vial, G. (2019) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2019.01.003 · Cited by 7,337
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Negative Self-Efficacy and Goal Effects Revisited
Bandura, A., & Locke, E. A. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.1.87 · Cited by 2,813
Park, S. Y. (2009) · Educational Technology & Society · Cited by 1,385
Loneliness and social isolation during the COVID-19 pandemic
Hwang, T.-J., Rabheru, K., Peisah, C., Reichman, W., & Ikeda, M. (2020) · International Psychogeriatrics · doi:10.1017/s1041610220000988 · Cited by 1,044 · cited 1×
“Recently, the educational community has recognized AI’s potential to facilitate learning in various contexts (Hwang et al. 2020).”
BackgroundChao, C.-M. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.01652 · Cited by 1,041
Research works printed but not linked: 4
- Ekin, C. Ç. 2022. Eğitimde yapay zeka uygulamaları ve zeki öğretim sistemleri [Artificial intelligence applications and smart teaching systems in education]. Eğitimde Dijitalleşme ve Yeni Yaklaşımlar. Istanbul: Efe Akademi Puplication.
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- Shen, C., and H. Chuang. 2010. Exploring users’ attitudes and intentions toward the interactive whiteboard technology environment. International Review on Computers and Software 5:200–08.
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Cited by
Sorted by citations
ChatGPT in higher education learning: Acceptance and use
Habibi, A., Muhaimin, M., Danibao, B. K., Wibowo, Y. G., Wahyuni, S., & Octavia, A. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100190 · Cited by 214
Acosta-Enriquez, B. G., Arbulú Ballesteros, M. A., Huamaní Jordan, O., López Roca, C., & Saavedra Tirado, K. (2024) · BMC Psychology · doi:10.1186/s40359-024-01764-z · Cited by 164
Peláez‐Sánchez, I. C., Velarde-Camaqui, D., & Glasserman‐Morales, L. D. (2024) · Frontiers in Education · doi:10.3389/feduc.2024.1392091 · Cited by 219
Adoption of Artificial Intelligence in Education: A Systematic Literature Review
Al-Momani, A. M., & Ramayah, T. (2024) · Studies in computational intelligence · doi:10.1007/978-3-031-61463-7_7 · Cited by 151
Acosta-Enriquez, B. G., Ramos-Farroñán, E. V., Zapata, L. V. V., García, F. S. M., Rabanal-León, H. C., Angaspilco, J. E. M., & Bocanegra, J. C. S. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e38315 · Cited by 151
Metadata
- Authors
- Alhwaiti, M.
- Affiliations
- Umm al-Qura University (SA)
- Corresponding author
- Alhwaiti, Mohammed
- ORCID
- Alhwaiti, Mohammed
- Venue
- Applied Artificial Intelligence
- Publisher
- Informa UK Limited
- Published
- 2023-02-22
- Volume
- 37
- Issue
- 1
- ISSN
- 0883-9514 (ISSN-L)
- 1087-6545
- OpenAlex
- W4321494359
- Cited by
- 105
- References
- 59
- Citations by year
- 2026: 27 · 2025: 36 · 2024: 31 · 2023: 11
- FWCI
- 26.91
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Applied Artificial Intelligence (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Psychology › Social Psychology › Technostress in Professional Settings
- Keywords
- artificial intelligence adoption, technology acceptance, UTAUT2 model, employee well-being, teacher self-efficacy, university faculty, higher education, post-COVID era, performance expectancy, effort expectancy, social influence, facilitating conditions, price value, habit
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