Artificial intelligence in higher education: Research notes from a longitudinal study
Higor Leite
Technological Forecasting and Social Change, 2025, vol. 215, issue C
Abstract:
Generative artificial intelligence (GenAI) has disrupted traditional educational approaches. Students are applying GenAI tools to access and create new content. However, the emergence of GenAI in higher education comes with caveats and academics and university administrators are learning to navigate this uncharted territory. GenAI is treated as a double-edged sword, with several benefits, such as innovation and productivity, but also drawbacks regarding ethics and academic misconduct. Therefore, our study aims to understand the impact of GenAI on students' experiences in the higher education ecosystem as students move to a new AI-enhanced job market. This research note article presents preliminary results from a 12-month longitudinal study with students interacting with GenAI. We conducted 35 semi-structured interviews and collected private diary entries (n = 108). Our results show six meaningful themes: Harnessing AI for Enhanced Academic Performance, AI Ethics and Trust Impact on Learning, GenAI as a Supplement to Human Work, Integration and Versatility of GenAI Tools, Balancing GenAI Limitations, and Navigating the AI Adoption Journey. The study also uses the transformative service research lens to present the transformative impact of GenAI in higher education. To contribute to practice and policymakers, we designed a research agenda to inform future studies on GenAI.
Keywords: Generative artificial intelligence; Higher education; Innovation; Technology; Transformative service research (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162525001465
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:215:y:2025:i:c:s0040162525001465
DOI: 10.1016/j.techfore.2025.124115
Access Statistics for this article
Technological Forecasting and Social Change is currently edited by Fred Phillips
More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().