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AI in higher education: Faculty perspective towards artificial intelligence through UTAUT approach

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  • Ryan Clifford L. Perez

    (Marinduque State College-Main Campus, Marindque)

Abstract

Applications of AI in higher education have been around for several years, and numerous studies have looked at the pedagogical potential that these applications can offer to support the learning processes. However, there are still concerns and misunderstandings about acceptance in higher education, particularly among faculty members, despite the growing number of studies and their opportunities for supporting the educational and learning process. This paper aims to investigate the Behavioral Intention (BI) of Higher Education Institution faculty (HEI-faculty) towards adopting AI from a pedagogical perspective. The hypotheses in this paper were tested using a technology acceptance model with four major constructs: Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC), as well as the effects of four mediating variables: age, gender, experience, and voluntariness. The result has shown that the Behavioral Intention (BI) of adopting AI among HEI faculty has a strong positive significant correlation with PE, EE, SI, and FC. Interestingly, the social influence of adopting AI from colleagues has a strong influence on the use of AI for education. Thus, one of the proposed hypotheses was disproven. Furthermore, the result of this paper also suggests considerations for the future development of AI applications for HE.

Suggested Citation

  • Ryan Clifford L. Perez, 2024. "AI in higher education: Faculty perspective towards artificial intelligence through UTAUT approach," HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - SOCIAL SCIENCES, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, vol. 14(4), pages 32-50.
    • Handle: RePEc:bjw:socien:v:14:y:2024:i:4:p:32-50
    DOI: 10.46223/HCMCOUJS.soci.en.14.4.2851.2024
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    References listed on IDEAS

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    1. Valentin Kuleto & Milena Ilić & Mihail Dumangiu & Marko Ranković & Oliva M. D. Martins & Dan Păun & Larisa Mihoreanu, 2021. "Exploring Opportunities and Challenges of Artificial Intelligence and Machine Learning in Higher Education Institutions," Sustainability, MDPI, vol. 13(18), pages 1-16, September.
    2. Alaa M. Momani, 2020. "The Unified Theory of Acceptance and Use of Technology: A New Approach in Technology Acceptance," International Journal of Sociotechnology and Knowledge Development (IJSKD), IGI Global, vol. 12(3), pages 79-98, July.
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