Perceptions of artificial intelligence in academic teaching and research: a qualitative study from AI experts and professors’ perspectives

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Detalles Bibliográficos
Publicado en:	International Journal of Educational Technology in Higher Education vol. 22, no. 1 (Dec 2025), p. 46
Autor principal:	Verboom, Ana Daniela Peres Rebelo
Otros Autores:	Pais, Leonor, Zijlstra, Fred R. H., Oswald, Frederick L., Santos, Nuno Rebelo dos
Publicado:	Springer Nature B.V.
Materias:	United Nations > UN Teaching Higher education Collaboration Professional development Automation Privacy Ethics Ethical standards System theory Accountability Skills Workers Artificial intelligence Sustainable development Employees Transparency Well being Integrated approach Surveillance Learning Digital technology Teacher attitudes College professors Interviews Professional training Policy making Occupational roles Academic work Optimism Principles Educational systems Qualitative research Teachers Attitudes Academic achievement Academic writing Work environment Systems approach Standards Research applications Administrators Economic Progress Professional Autonomy Institutional Autonomy Copyrights Skill Obsolescence Stakeholders Educational Research Influence of Technology Educational Technology Labor Social Systems Data Analysis Participant Satisfaction
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Descripción
Resumen:	Artificial Intelligence (AI) is significantly reshaping work settings, influencing the context, conditions, and content of various professional roles. It becomes crucial to assess AI’s effect on academic work. This study explores AI’s application within teaching and research tasks in academia. Specifically, it pursues two Objectives (1) to identify and describe both current and prospective AI systems in higher education, and (2) to characterize the opportunities and risks of integrating AI into academic environments. Interviews were conducted with 28 participants from Portugal, the Netherlands, and the United States. The questions addressed AI’s influence on Ethical Principles and Decent Work Dimensions. Results were analyzed considering the Socio-Technical Systems Approach. Interviews were coded, analyzed for sentiment, and clustered into seven participant profiles based on coding similarities: “Optimists,” “Moderates,” “Dreamers,” “Cautious Skeptics,” “Expansionists,” “Knowledgeable,” and “Strategists.” Findings emphasize the importance of aligning technology and human needs to achieve successful AI integration. They also point to the value of well-defined guidelines, fair funding, and continuous professional development. By illustrating the spectrum of attitudes and readiness levels among academic stakeholders, this study offers key insights for policymakers, administrators, and educators seeking to embrace AI while preserving Ethical Principles and Decent Work standards.
ISSN:	2365-9440 1698-580X
DOI:	10.1186/s41239-025-00546-w
Fuente:	Political Science Database