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Cited by 47Artificial Intelligence in EducationArtificial Intelligence in Healthcare and EducationIntelligent Tutoring Systems and Adaptive Learning

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Students’ perceived impact of GenAI tools on learning and assessment in higher education: the role of individual AI competence

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Heil, Joana, Ifenthaler, Dirk, Cooper, Martin, Mascia, Maria Lidia, Conti, Rachele, Penna, Maria Pietronilla·2025·Smart Learning Environments
DOI 10.1186/s40561-025-00395-0
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Abstract

The adoption of artificial intelligence (AI) and generative artificial intelligence (GenAI) tools in higher education institutions (HEIs) raises numerous questions and application possibilities. This study included N = 223 students from HEIs across different countries and investigated students’ AI competence and how they evaluated the specific benefits of several GenAI tools for learning and assessment. The GenAI tools included in the study were designed for different application contexts and purposes. The study goes beyond students’ preferences by simultaneously adopting a broad approach that considers their AI competence, their perspectives on six different GenAI tools, and a focused approach that investigates the specific benefits of these tools in learning and assessment. The results indicate that the dimensions of AI competence vary considerably, significantly impacting how the GenAI tools were evaluated. Results also show that students perceived and evaluated the different tools according to their potential use in pursuing their study goals. This research calls for a more nuanced and differentiated analysis of AI approaches by different stakeholders in HEIs for the promotion of the enhancement of students’ AI competence and awareness in using GenAI tools rather than amalgamating AI and GenAI tools under one banner and for understanding possible benefits and application of them in HE learning and assessment processes.

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  • GenAI-empowered assessment systems dynamically adapt to individual learners by diagnosing misconceptions and suggesting personalized learning pathways.

    “GenAI-empowered assessment systems dynamically adapt to individual learners by utilizing sophisticated algorithms, diagnosing misconceptions, and suggesting personalized learning pathways (Heil et al., 2025 ; Zhu & Zhang, 2025 ).”

    From Socratic Mind: Impact of a Novel GenAI-Powered Formative Assessment Tool on Student Learning and Higher-Order Thinking (2026) · cites this paper as Heil et al., 2025

    The Introduction (page not provided) describes AI’s potential to personalise learning and provide adaptive support, while “Generative artificial intelligence for assessment” says GenAI-supported assessment may involve adaptive learning. Neither passage says these systems diagnose misconceptions or suggest personalised learning pathways; the paper presents adaptation as a possibility, not an established system capability. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

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Metadata

Authors
Heil, J., Ifenthaler, D., Cooper, M., Mascia, M. L., Conti, R., & Penna, M. P.
Affiliations
  • University of Mannheim (DE)
  • Curtin University (AU)
  • University of Sassari (IT)
  • University of Cagliari (IT)
Corresponding author
Ifenthaler, Dirk
ORCID
Venue
Smart Learning Environments
Publisher
Springer Science and Business Media LLC
Published
2025-05-30
Volume
12
Issue
1
ISSN
2196-7091 (ISSN-L)
DOI
10.1186/s40561-025-00395-0
OpenAlex
W4410907159
Cited by
47
References
24
Citations by year
2026: 40 · 2025: 7
FWCI
38.94
Type
journal article
Language
en
Open access
Licence
Locations
  • Smart Learning Environments (publishedVersion, cc-by)
  • MADOC (University of Mannheim) (acceptedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • UnissResearch (Università degli Studi di Sassari) (submittedVersion)
Funders
Universität Mannheim
Topics
  • Social Sciences › Education › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Keywords
generative AI, AI competencies, student perceptions, higher education, assessment and learning, artificial intelligence in education

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