A longitudinal study on artificial intelligence adoption: understanding the drivers of ChatGPT usage behavior change in higher education
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As the field of artificial intelligence (AI) continues to progress, the use of AI-powered chatbots, such as ChatGPT, in higher education settings has gained significant attention. This paper addresses a well-defined problem pertaining to the critical need for a comprehensive examination of students' ChatGPT adoption in higher education. To examine such adoption, it is imperative to focus on measuring actual user behavior. While measuring students' ChatGPT usage behavior at a specific point in time can be valuable, a more holistic approach is necessary to understand the temporal dynamics of AI adoption. To address this need, a longitudinal survey was conducted, examining how students' ChatGPT usage behavior changes over time among students, and unveiling the drivers of such behavior change. The empirical examination of 222 Dutch higher education students revealed a significant decline in students' ChatGPT usage behavior over an 8 month period. This period was defined by two distinct data collection phases: the initial phase (T1) and a follow-up phase conducted 8 months later (T2). Furthermore, the results demonstrate that changes in trust, emotional creepiness, and Perceived Behavioral Control significantly predicted the observed change in usage behavior. The findings of this research carry significant academic and managerial implications, as they advance our comprehension of the temporal aspects of AI adoption in higher education. The findings also provide actionable guidance for AI developers and educational institutions seeking to optimize student engagement with AI technologies.
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Polyportis (2024) observed that as students grew more accustomed to ChatGPT, their feelings of emotional creepiness diminished, but their trust levels decreased, leading to decreased usage.
“Polyportis (2024) observes that as students grew more accustomed to ChatGPT, their feelings of emotional creepiness (i.e., the unsettling emotions or discomfort that individuals may encounter when interacting with AI systems that mimic human emotions or intentions) diminished, but their trust levels decreased, leading to decreased usage.”
From Fostering AI Literacy in Undergraduates: A ChatGPT Workshop Case Study (2025) · cites this paper as Polyportis (2024)
The Results (§3.3) show that emotional creepiness, trust, and ChatGPT usage all declined between T1 and T2; the Discussion (§4.1) associates reduced creepiness with greater familiarity. Changes in trust positively predicted changes in usage, but the paper reports an association, not proof that declining trust caused the overall drop in usage. It also finds that reduced creepiness predicted increased, rather than decreased, usage. (LLM, conf=0.85)
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- Authors
- Polyportis, A.
- Affiliations
- Delft University of Technology (NL)
- Corresponding author
- Polyportis, Athanasios
- Venue
- Frontiers in Artificial Intelligence
- Publisher
- Frontiers Media SA
- Published
- 2024-01-05
- Volume
- 6
- Pages
- 1324398-1324398
- ISSN
- 2624-8212 (ISSN-L)
- PMC
- PMC10797058
- OpenAlex
- W4390610074
- Cited by
- 111
- References
- 56
- Citations by year
- 2026: 58 · 2025: 36 · 2024: 17
- FWCI
- 41.74
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Artificial Intelligence (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Research Repository (Delft University of Technology) (submittedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- ChatGPT, artificial intelligence adoption, university students, trust in AI, perceived behavioral control, student engagement with AI
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