Professors versus Students: An Introductive Bibliometric Review of AI Acceptance in Higher Education's Specialisations of Tertiary Sector

Luciana-Floriana Poenaru, Delia Popescu, Remus-Ion Hornoiu and Giuseppe Lanfranchi
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Luciana-Floriana Poenaru: Bucharest University of Economic Studies, Bucharest, Romania
Delia Popescu: Bucharest University of Economic Studies, Bucharest, Romania
Remus-Ion Hornoiu: Bucharest University of Economic Studies, Bucharest, Romania
Giuseppe Lanfranchi: University of Messina, Messina, Italy

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ECONOMICS AND SOCIAL SCIENCES, 2024, vol. 6, issue 1, 326-335

Abstract: The increasing development of artificial intelligence (AI) technology has raised considerable interest in its application within educational environments, particularly in higher education. This study examines the dynamics of AI technology acceptance among service sector academia with the intent of delineating the critical determinants that influence its adoption and utilisation. Emphasising a comparative analysis, this investigation juxtaposes the perceptions of both students and professors. A systematic keyword search was implemented to evaluate pertinent studies encompassing these determinants, in conjunction with relevant theoretical constructs and academic fields. Although the existing literature offers substantial information on AI adoption factors within the service sector, a lacuna persists in understanding the variables and conceptual frameworks that characterise the acceptance of AI technology in higher education in the service sector. Identifying these drivers of adoption could be of great benefit to students, professors, but mostly to policy-makers who are poised to devise and execute strategic initiatives advocating for the seamless integration of AI into pedagogy, scholarly inquiry, and the broader academic field.

Keywords: artificial intelligence; technology acceptance models; higher education; professors; students. (search for similar items in EconPapers)
JEL-codes: I23 O14 O33 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:rom:conase:v:6:y:2024:i:1:p:326-335

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