{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T15:35:01Z","timestamp":1782401701712,"version":"3.54.5"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T00:00:00Z","timestamp":1731283200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T00:00:00Z","timestamp":1731283200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100003504","name":"University of the Western Cape","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003504","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Educ Inf Technol"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>This study examines the influence of AI-powered and emerging technologies on pedagogical practices in higher education, focusing on their role on behavioural intention (BI) and actual usage among educators and students. The research hypothesises that the relationship between each Unified Theory of Acceptance and Use of Technology (UTAUT) constructs - Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC) - and BI to use AI is mediated by Attitude towards AI. Additionally, it explores the mediation of the relationship between Technological, Organisational, and Environmental (TOE) framework and BI to use AI by Attitude towards AI. Furthermore, it hypothesises that the relationship between UTAUT constructs, and the actual Usage of AI is mediated by BI. Data were collected from 115 respondents through a survey measuring perceptions of UTAUT and technology-organisation-Environment (TOE) constructs. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to analyse the data, alongside PLS-Multi-Group Analysis (PLS-MGA) to explore gender differences. The key results indicated that PE and EE significantly influenced Attitude towards AI (F\u2009=\u200914.861 and F\u2009=\u200933.887, respectively), which in turn significantly influenced BI (\u03b2\u2009=\u20090.468, t\u2009=\u20095.106). However, SI had an insignificant effect (F\u2009=\u20090.346), and FC had a minimal influence (F\u2009=\u20092.225). The study found that Organisational Context played a significant role in shaping Attitude towards AI, influencing BI, whereas the direct influence of TOE on BI was not significant (F\u2009=\u20091.356), indicating full mediation by Attitude. Additionally, higher BI did not necessarily translate to increased AI usage (\u03b2 = -0.381, t\u2009=\u20094.749), suggesting external barriers or moderating factors. These findings provide valuable insights for developing strategies to enhance AI-driven pedagogical innovations, emphasising the importance of fostering positive attitudes and addressing practical challenges in AI adoption.<\/jats:p>","DOI":"10.1007\/s10639-024-13122-y","type":"journal-article","created":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T08:36:23Z","timestamp":1731314183000},"page":"1045-1072","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["Leveraging AI-enhanced and emerging technologies for pedagogical innovations in higher education"],"prefix":"10.1007","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0283-0262","authenticated-orcid":false,"given":"Anass","family":"Bayaga","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,11,11]]},"reference":[{"issue":"1","key":"13122_CR2","doi-asserted-by":"publisher","first-page":"23","DOI":"10.4314\/ajlais.v34i1.2","volume":"34","author":"T Abba","year":"2024","unstructured":"Abba, T. (2024). Use of Artificial Intelligence Technologies in Rendering Library services: An empirical evidence from University Libraries in Africa. African Journal of Library Archives and Information Science, 34(1), 23\u201335. https:\/\/doi.org\/10.4314\/ajlais.v34i1.2","journal-title":"African Journal of Library Archives and Information Science"},{"key":"13122_CR1","doi-asserted-by":"publisher","first-page":"7205","DOI":"10.1007\/s10639-021-10464-y","volume":"26","author":"MM Abbad","year":"2021","unstructured":"Abbad, M. M. (2021). Using the UTAUT model to understand students\u2019 usage of e-learning systems in developing countries. 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