Modelling the influence of antecedents of artificial intelligence on academic productivity in higher education: a mixed method approach

Guardado en:
Detalles Bibliográficos
Publicado en:Cogent Education vol. 11, no. 1 (Jan 2024)
Autor principal: Moses Segbenya
Otros Autores: Senyametor, Felix, Simon-Peter, Kafui Aheto, Agormedah, Edmond Kwesi, Nkrumah, Kwame, Kaedebi-Donkor, Rebecca
Publicado:
Taylor & Francis Ltd.
Materias:
Acceso en línea:Citation/Abstract
Full Text - PDF
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!

MARC

LEADER 00000nab a2200000uu 4500
001 3158495080
003 UK-CbPIL
022 |a 2331-186X 
024 7 |a 10.1080/2331186X.2024.2387943  |2 doi 
035 |a 3158495080 
045 2 |b d20240101  |b d20240131 
084 |a 283735  |2 nlm 
100 1 |a Moses Segbenya  |u Department of Business Programmes, College of Distance Education, University of Cape Coast, Cape Coast, Ghana 
245 1 |a Modelling the influence of antecedents of artificial intelligence on academic productivity in higher education: a mixed method approach 
260 |b Taylor & Francis Ltd.  |c Jan 2024 
513 |a Journal Article 
520 3 |a This study examined the effect of antecedents of artificial intelligence (AI) on the productivity of academics in higher education. The study was guided by the pragmatic epistemic perspective predicated on the concurrent integrated mixed-method design used with the support of a Google softcopy version of the semi-structured questionnaire (closed and open-ended questions) to collect data from 663 academics from higher educational institutions in Ghana, Nigeria, South Africa, Mexico, Germany, India, and Uganda. The quantitative data were analysed with descriptive and inferential statistical tools while thematic pattern matching was engaged to analyse the qualitative data. The study found that academics hardly use the main AI tools/platforms, and those mainly used for research and teaching-related activities were ChatGPT, OpenAI, and Quillbot. These AI tools were used mostly for general searches for information on course-related concepts, course materials, and plagiarism checks among others. The study further revealed that challenges associated with AI usage influenced the productivity of academics significantly. Finally, the availability of AI tools was found to engender AI usage but does not directly translate into the productivity of academics. The study, therefore, recommended that the management of higher educational institutions espouse policies, and provide timely information and training on the use of AI in higher education. The policies, information, and training provided should specifically address how to adopt different AI tools for specific aspects of teaching tailored and gravitated toward catalysing the productivity of academics. 
653 |a Higher education 
653 |a Artificial intelligence 
653 |a Productivity 
653 |a Course Content 
700 1 |a Senyametor, Felix  |u Department of Education and Psychology, University of Cape Coast, Cape Coast, Ghana 
700 1 |a Simon-Peter, Kafui Aheto  |u Department of Distance Education, School of Continuing & Distance Education, University of Ghana, Legon, Accra, Ghana 
700 1 |a Agormedah, Edmond Kwesi  |u Department of Business & Social Sciences Education, Faculty of Humanities and Social Sciences Education, University of Cape Coast, Cape Coast, Ghana 
700 1 |a Nkrumah, Kwame  |u Department of Education, College of Distance Education, University of Cape Coast, Cape Coast, Ghana 
700 1 |a Kaedebi-Donkor, Rebecca  |u Department of Education and Psychology, Faculty of Educational Foundations, University of Cape Coast, Cape Coast, Ghana 
773 0 |t Cogent Education  |g vol. 11, no. 1 (Jan 2024) 
786 0 |d ProQuest  |t Education Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3158495080/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3158495080/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch