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 DOI Creative Commons
Sasha Nikolic, Isabelle Wentworth, Lynn Sheridan

et al.

Australasian Journal of Educational Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 16, 2024

The rapid advancement of artificial intelligence (AI) has outpaced existing research and regulatory frameworks in higher education, leading to varied institutional responses. Although some educators institutions have embraced AI generative (GenAI), other individuals remain cautious. This systematic literature review explored teaching academics' attitudes, perceptions intentions towards GenAI, identifying perceived benefits obstacles. Utilising the unified theory acceptance use technology framework, this study reveals positive attitudes AI's efficiency enhancement, but also significant concerns about academic integrity, accuracy, reliability, skill development need for comprehensive training policies. These findings underscore necessity support navigate integration GenAI tertiary education. Implications practice or policy: Attitudes are diverse with recognising raising ethical practical concerns. indicate a more understanding dialogue within communities. Academics' these technologies contingent upon robust guidelines supportive Institutional shape behaviours. scarcity formal training, policy currently limits effective integration.

Language: Английский

A Systematic Review of Responses, Attitudes, and Utilization Behaviors on Generative AI for Teaching and Learning in Higher Education DOI Creative Commons
Fan Wu,

Yang Dang,

Manli Li

et al.

Behavioral Sciences, Journal Year: 2025, Volume and Issue: 15(4), P. 467 - 467

Published: April 4, 2025

The utilization of Generative AI (GenAI) in higher education classrooms has significantly increased recent years. Studies show that GenAI holds promise impacting the learning experiences both students and teachers, offering personalized assessment opportunities. This study conducts a systematic review responses, attitudes, behaviors related to application within classrooms. To this end, we synthesized 99 papers published between 2020 August 2024, focusing on settings. analysis addresses three key inquiries: behaviors. provides an updated understanding from psychological perspectives GenAI’s role teaching processes education, with particular emphasis technologies.

Language: Английский

Citations

0
Will AI-enabled Conversational Agents Acting as Digital Employees Enhance Employee Job Identity? DOI Creative Commons
Wenting Wang, Rick D. Hackett, Norm Archer

et al.

Information & Management, Journal Year: 2025, Volume and Issue: unknown, P. 104099 - 104099

Published: Jan. 1, 2025

Language: Английский

Citations

0
Project-work Artificial Intelligence Integration Framework (PAIIF): Developing a CDIO-based framework for educational integration DOI Creative Commons
Sasha Nikolic,

Zach Quince,

Anna Lindqvist

et al.

STEM Education, Journal Year: 2025, Volume and Issue: 5(2), P. 310 - 332

Published: Jan. 1, 2025

Language: Английский

Citations

0
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 DOI Creative Commons
Sasha Nikolic, Isabelle Wentworth, Lynn Sheridan

et al.

Australasian Journal of Educational Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 16, 2024

The rapid advancement of artificial intelligence (AI) has outpaced existing research and regulatory frameworks in higher education, leading to varied institutional responses. Although some educators institutions have embraced AI generative (GenAI), other individuals remain cautious. This systematic literature review explored teaching academics' attitudes, perceptions intentions towards GenAI, identifying perceived benefits obstacles. Utilising the unified theory acceptance use technology framework, this study reveals positive attitudes AI's efficiency enhancement, but also significant concerns about academic integrity, accuracy, reliability, skill development need for comprehensive training policies. These findings underscore necessity support navigate integration GenAI tertiary education. Implications practice or policy: Attitudes are diverse with recognising raising ethical practical concerns. indicate a more understanding dialogue within communities. Academics' these technologies contingent upon robust guidelines supportive Institutional shape behaviours. scarcity formal training, policy currently limits effective integration.

Language: Английский

Citations

2