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Cited by 11Artificial Intelligence in Healthcare and EducationArtificial Intelligence in EducationDigital literacy in education

Studying with GenAI: cross-sectional study on usage patterns, needs, competencies, and ethical perspectives of medical informatics students

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Jongkind, Remco, Bikker, Yurrian, Meinema, Jennita, Broens, Tom·2025·Frontiers in Education
DOI 10.3389/feduc.2025.1658415
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Abstract

Background: Generative AI use (GenAI) by students is transforming education and professional practice, necessitating literacy training. Comprehensive data on usage, competencies, needs and ethics, especially in the Netherlands, is scarce. To inform future literacy education, this study examines usage frequency and type, self-assessed competencies, ethical attitudes, and perceived career impact among Medical Informatics students at the University of Amsterdam. Methods: From September 2024 to February 2025, we conducted a cross-sectional survey among Bachelor and Master students. Eighty-six percent of the 155 students completed a questionnaire based on the EU's DigComp 2.2 framework. Items (Likert scale and multiple-choice) assessed GenAI usage frequency and purposes, tool types, paid subscription use, critical evaluation capabilities, prompting proficiency, ethical concerns (privacy, bias, environmental impact, copyright), and perceived effects on academic behavior and career outlook. Results: Daily use grew from 5% among first-years to 33% of Msc students. Paid subscriptions rose from 2.4% in first-year to 38% in second-year Master's students. ChatGPT was used by >90%. Educational use included brainstorming (56%−75%), summarizing (50%−76%), and text rewriting (44%−70%), coding assistance increased after the first year (16% vs. 44%−67% in later cohorts). Reliance on GenAI over traditional resources peaked in third-year undergraduates (45.8% agreement) vs. first year (9.1%). Competency ratings varied: Critical evaluation was high (60%−85% agreement). Prompting proficiency was moderate (35%−68%). Ethical appraisal was low (15%−56%). Competence in GenAI-assisted tasks (code writing, essay composition, practice question creation) was lowest among first-year (16%−38%) and highest in advanced cohorts (33%−83%). Privacy was the top ethical concern (46%−76%), followed by effects on skill development (38%−63%) and bias (33%−100%). Copyright (12%−46%) and environmental impact (13%−28%) received less concern. Interest in learning centered on prompting (58%−84%), privacy/security (60%−84%), and bias mitigation (38%−88%). Sixteen percent to thirty percent of students feared a negative impact of GenAI on their career perspectives. Conclusion: Students increasingly use GenAI as a complementary academic resource but exhibit skill gaps in ethical safety practices and content creation. Institutions should ensure equitable, secure GenAI infrastructure and integrate ethics-centered AI literacy in the curriculum.

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Research works printed but not linked: 3

  1. Corbin, T., Dawson, P., and Liu, D. (2025). Talk is cheap: why structural assessment changes are needed for a time of GenAI. Assess. Eval. High. Educ. 1-11. doi: 10.1080/02602938.2025.2503964 Available online at: https://www.tandfonline. com/doi/full/10.1080/02602938.2025.2503964?scroll=top&needAccess=true · DOI · Paper page
  2. 1121 · DOI · Paper page
  3. Vuorikari, R., Kluzer, S., and Punie, Y. (2022). DigComp 2.2: The Digital Competence Framework for Citizens -With new examples of knowledge, skills and attitudes [WWW Document]. JRC Publ. Repos. doi: 10.2760/115376 · DOI

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Authors
Jongkind, R., Bikker, Y., Meinema, J., & Broens, T.
Affiliations
Amsterdam University Medical Centers (NL)
Corresponding author
Jongkind, Remco
ORCID
Venue
Frontiers in Education
Publisher
Frontiers Media SA
Published
2025-09-19
Volume
10
ISSN
2504-284X (ISSN-L)
DOI
10.3389/feduc.2025.1658415
OpenAlex
W4414366094
Cited by
11
References
24
Citations by year
2026: 11
FWCI
2.67
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Education (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Pure Amsterdam UMC (submittedVersion, cc-by)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Information Systems › Digital literacy in education
Keywords
generative AI, AI literacy, AI competencies, AI ethics, privacy concerns, algorithmic bias, copyright, environmental impact of AI, critical appraisal, career impact, DigComp 2.2, ChatGPT, AI-assisted programming, artificial intelligence in education, student attitudes toward AI

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