The impact of TPACK on teachers’ willingness to integrate generative artificial intelligence (GenAI): The moderating role of negative emotions and the buffering effects of need satisfaction DOI

Yiming Yang,

Qi Xia,

C. C. Liu

и другие.

Teaching and Teacher Education, Год журнала: 2024, Номер 154, С. 104877 - 104877

Опубликована: Ноя. 26, 2024

Язык: Английский

Exploring the Impact of Generative AI on Peer Review: Insights from Journal Reviewers DOI Creative Commons
Saman Ebadi, Hassan Nejadghanbar,

Ahmed Rawdhan Salman

и другие.

Journal of Academic Ethics, Год журнала: 2025, Номер unknown

Опубликована: Фев. 11, 2025

Язык: Английский

Процитировано

2

Research Data Management and Crowdsourcing Personal Histories DOI Creative Commons
Catherine Conisbee

Journal of Open Humanities Data, Год журнала: 2025, Номер 11

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Emotional (Dis/Un)entanglement in Becoming an Academic in the Neoliberal Era: Dialogising Transnational Accounts of Being, Thinking and Feeling DOI Creative Commons
Mahtab Janfada,

Angel M. Y. Lin,

Fei Victor Lim

и другие.

International Journal of Applied Linguistics, Год журнала: 2025, Номер unknown

Опубликована: Март 12, 2025

ABSTRACT This paper explores the complex emotions and affective challenges that academics might experience in their journey of becoming within neoliberal higher education contexts transnationally. These are examined entanglement with intricate social, ideological, political racial factors across different stages academic careers. Informed by a theoretical conceptual framework relation to affect agency plurilingual through dialogic methodology, diverse accounts four transnational language presented series embodied or online, synchronous asynchronous events explore embrace entangled emotions. Instead offering an instrumental solution for these challenging feelings, authors attempted untangle emotional being, thinking feeling scenarios put forth agentive approach richer more sustainable process era.

Язык: Английский

Процитировано

0

Examining predictors of generative-AI acceptance and usage in academic research: a sequential mixed-methods approach DOI
Sushma Verma, Neerja Kashive, Ashish Gupta

и другие.

Benchmarking An International Journal, Год журнала: 2025, Номер unknown

Опубликована: Март 24, 2025

Purpose This research uses a mixed-methods approach to identify predictors of Generative artificial intelligence (Gen-AI) adoption and usage among academics educational researchers. It examines drivers barriers based on the diffusion innovation theory (DIT) planned behaviour (TPB). Design/methodology/approach A qualitative investigation was carried out by conducting interviews academic researchers who used Gen-AI tools such as ChatGPT. Based DIT, TPB analysis results, an integrated model proposed tested using survey data collected from analysed partial least squares-structural equation modelling (PLS-SEM). Findings The study demonstrated that relative advantages observability influence attitude subjective norms, these in turn impact behavioural intentions. Researchers' perception advantage their intentions use were found lead positive behaviours. However, technical limitations ethical concerns acted key moderators between intention norms intention, respectively. Mediation effects also observed. Research limitations/implications utilised DIT its base models, future could incorporate additional constructs other technology theories. concentrated had subsequently reported significant factors affecting usage. Future studies should consider perspective non-users tools. Further, geographical focus India, broaden scope. Practical implications community must unite develop guidelines for plagiarism research. be emphasising importance highlights need establishing standards, comprehensive transparently within framework. Originality/value results can greatly enhance understanding researchers, particularly light about integrity potential negative consequences

Язык: Английский

Процитировано

0

The impact of TPACK on teachers’ willingness to integrate generative artificial intelligence (GenAI): The moderating role of negative emotions and the buffering effects of need satisfaction DOI

Yiming Yang,

Qi Xia,

C. C. Liu

и другие.

Teaching and Teacher Education, Год журнала: 2024, Номер 154, С. 104877 - 104877

Опубликована: Ноя. 26, 2024

Язык: Английский

Процитировано

2