Acceptance of Artificial Intelligence as a Teaching Strategy Among University Professors: The Role of Habit, Hedonic Motivation, and Competence for Technology Integration
The immersion of artificial intelligence (AI) in higher education presents significant challenges and opportunities. This study examines the acceptance of AI as a teaching strategy among university teachers, following the extended UTAUT2 model with the inclusion of the teacher skills and knowledge f...
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Human Behavior and Emerging Technologies |
| Online Access: | http://dx.doi.org/10.1155/hbe2/5933157 |
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| author | Benicio Gonzalo Acosta-Enriquez Luigi Italo Villena Zapata Olger Huamaní Jordan Carlos López Roca Betty Margarita Cabrera Cipirán Willy Saavedra Villacrez Carmen Graciela Arbulu Perez Vargas |
| author_facet | Benicio Gonzalo Acosta-Enriquez Luigi Italo Villena Zapata Olger Huamaní Jordan Carlos López Roca Betty Margarita Cabrera Cipirán Willy Saavedra Villacrez Carmen Graciela Arbulu Perez Vargas |
| author_sort | Benicio Gonzalo Acosta-Enriquez |
| collection | DOAJ |
| description | The immersion of artificial intelligence (AI) in higher education presents significant challenges and opportunities. This study examines the acceptance of AI as a teaching strategy among university teachers, following the extended UTAUT2 model with the inclusion of the teacher skills and knowledge for technology integration (SKTI) construct. Employing a quantitative cross-sectional research design, data were collected from 318 university teachers with prior experience using AI as a learning strategy through nonprobabilistic convenience sampling across 10 universities in northern Peru. Participants completed an online survey, and data were analyzed using descriptive statistics, Kruskal–Wallis tests with Dunn’s post hoc comparisons, and partial least squares structural equation modeling (PLS-SEM). The results showed that performance expectancy (β=0.129∗∗), hedonic motivation (β=0.167∗∗), habit (β=0.405∗∗∗), and SKTI (β=0.263∗∗∗) had a positive influence on the behavioral intention to adopt AI as a teaching strategy. Additionally, behavioral intention (β=0.303∗∗∗), facilitating conditions (β=0.115∗), and habit (β=0.464∗∗) determine the behavioral use of AI by teachers. The Kruskal–Wallis test revealed significant differences among age groups in the performance expectancy, social influence, habit, and behavioral intention constructs, with the 37- to 48-year-old age group showing higher average ranks. The discussion highlights that these findings suggest a positive adoption of AI among teachers, driven by individual and contextual factors, and challenges assumptions about the relevance of certain constructs in this specific context. In conclusion, this study represents a significant advancement in understanding the adoption of AI in university teaching and provides valuable guidance for practical implementation efforts. |
| format | Article |
| id | doaj-art-5d6320c53bd5466394b56884c1eadd94 |
| institution | Kabale University |
| issn | 2578-1863 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Human Behavior and Emerging Technologies |
| spelling | doaj-art-5d6320c53bd5466394b56884c1eadd942025-08-20T03:40:21ZengWileyHuman Behavior and Emerging Technologies2578-18632025-01-01202510.1155/hbe2/5933157Acceptance of Artificial Intelligence as a Teaching Strategy Among University Professors: The Role of Habit, Hedonic Motivation, and Competence for Technology IntegrationBenicio Gonzalo Acosta-Enriquez0Luigi Italo Villena Zapata1Olger Huamaní Jordan2Carlos López Roca3Betty Margarita Cabrera Cipirán4Willy Saavedra Villacrez5Carmen Graciela Arbulu Perez Vargas6Departamento de Ciencias PsicológicasDepartamento de CienciasDepartamento de PsicologíaFacultad de educaciónDepartamento de Ciencias PsicológicasPosgrado en EducaciónEscuela de PosgradoThe immersion of artificial intelligence (AI) in higher education presents significant challenges and opportunities. This study examines the acceptance of AI as a teaching strategy among university teachers, following the extended UTAUT2 model with the inclusion of the teacher skills and knowledge for technology integration (SKTI) construct. Employing a quantitative cross-sectional research design, data were collected from 318 university teachers with prior experience using AI as a learning strategy through nonprobabilistic convenience sampling across 10 universities in northern Peru. Participants completed an online survey, and data were analyzed using descriptive statistics, Kruskal–Wallis tests with Dunn’s post hoc comparisons, and partial least squares structural equation modeling (PLS-SEM). The results showed that performance expectancy (β=0.129∗∗), hedonic motivation (β=0.167∗∗), habit (β=0.405∗∗∗), and SKTI (β=0.263∗∗∗) had a positive influence on the behavioral intention to adopt AI as a teaching strategy. Additionally, behavioral intention (β=0.303∗∗∗), facilitating conditions (β=0.115∗), and habit (β=0.464∗∗) determine the behavioral use of AI by teachers. The Kruskal–Wallis test revealed significant differences among age groups in the performance expectancy, social influence, habit, and behavioral intention constructs, with the 37- to 48-year-old age group showing higher average ranks. The discussion highlights that these findings suggest a positive adoption of AI among teachers, driven by individual and contextual factors, and challenges assumptions about the relevance of certain constructs in this specific context. In conclusion, this study represents a significant advancement in understanding the adoption of AI in university teaching and provides valuable guidance for practical implementation efforts.http://dx.doi.org/10.1155/hbe2/5933157 |
| spellingShingle | Benicio Gonzalo Acosta-Enriquez Luigi Italo Villena Zapata Olger Huamaní Jordan Carlos López Roca Betty Margarita Cabrera Cipirán Willy Saavedra Villacrez Carmen Graciela Arbulu Perez Vargas Acceptance of Artificial Intelligence as a Teaching Strategy Among University Professors: The Role of Habit, Hedonic Motivation, and Competence for Technology Integration Human Behavior and Emerging Technologies |
| title | Acceptance of Artificial Intelligence as a Teaching Strategy Among University Professors: The Role of Habit, Hedonic Motivation, and Competence for Technology Integration |
| title_full | Acceptance of Artificial Intelligence as a Teaching Strategy Among University Professors: The Role of Habit, Hedonic Motivation, and Competence for Technology Integration |
| title_fullStr | Acceptance of Artificial Intelligence as a Teaching Strategy Among University Professors: The Role of Habit, Hedonic Motivation, and Competence for Technology Integration |
| title_full_unstemmed | Acceptance of Artificial Intelligence as a Teaching Strategy Among University Professors: The Role of Habit, Hedonic Motivation, and Competence for Technology Integration |
| title_short | Acceptance of Artificial Intelligence as a Teaching Strategy Among University Professors: The Role of Habit, Hedonic Motivation, and Competence for Technology Integration |
| title_sort | acceptance of artificial intelligence as a teaching strategy among university professors the role of habit hedonic motivation and competence for technology integration |
| url | http://dx.doi.org/10.1155/hbe2/5933157 |
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