AI-Enhanced Teaching Tools in Higher Education: A Literature and Requirements Analysis
Abstract
This paper presents a comprehensive literature and requirements analysis of AI-enhanced teaching tools in higher education. Through systematic review of recent publications, we examine current AI applications in university teaching including chatbots, virtual teaching assistants, intelligent tutoring systems, and adaptive learning platforms. While these tools are increasingly deployed, the literature reveals a critical gap: implementation requirements remain largely unspecified. We address this by deriving essential requirements across technological, ethical, organizational, and pedagogical dimensions, alongside necessary metadata standards. Our analysis demonstrates that successful AI adoption demands holistic institutional transformation encompassing governance frameworks, professional development, and standardized data schemas, not merely technological deployment. This study provides universities with an evidence-based implementation roadmap while establishing foundations for future empirical research on AI-enhanced teaching effectiveness.
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Bauer, L., Slatvitskaya, A., Steegmüller, T., Langer, Y., Lanquillon, C. (2025). AI-Enhanced Teaching Tools in Higher Education: A Literature and Requirements Analysis. 13th Higher Education Institutions Conference (HEIC 2025), 04-05 September, 2025, Dubrovnik (Croatia). https://doi.org/10.66781/heic.2025.05
