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Perspectives of academic staff on artificial intelligence in higher education: exploring areas of relevance

Dana-Kristin Mah, Nils Knoth, Marc Egloffstein

2025Frontiers in Education11 citationsDOIOpen Access PDF

Abstract

Despite the recent increase in research on artificial intelligence in education (AIED), studies investigating the perspectives of academic staff and the implications for future-oriented teaching at higher education institutions remain scarce. This exploratory study provides initial insight into the perspectives of 112 academic staff by focusing on three aspects considered relevant for sustainable, future-oriented teaching in higher education in the age of AI: instructional design, domain specificity, and ethics. The results indicate that participants placed the greatest importance on AIED ethics. Furthermore, participants indicated a strong interest in (mandatory) professional development on AI and more comprehensive institutional support. Faculty who perceived AIED instructional design as important were more likely to use AI-based tools in their teaching practice. However, the perceived relevance of AIED domain specificity and ethics did not predict AI tool integration, which suggests an intention–behavior gap that warrants further investigation into factors such as AI literacy and structural conditions in higher education. The findings may serve as a basis for further discussion and development of adequate support services for higher education teaching and learning in the age of AI.

Topics & Concepts

Relevance (law)Knowledge managementEngineering managementHigher educationComputer scienceData scienceEngineering ethicsArtificial intelligenceEngineeringMathematics educationPsychologyPolitical scienceLawOnline Learning and AnalyticsEducational Innovations and ChallengesE-Learning and Knowledge Management
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