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Cited by 25Artificial Intelligence in EducationEducational Technology and PedagogyEFL/ESL Teaching and Learning

Exploring social and computer science students’ perceptions of AI integration in (foreign) language instruction

Open access
Dolenc, Kosta, Brumen, Mihaela·2024·Computers and Education: Artificial Intelligence
DOI 10.1016/j.caeai.2024.100285
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Abstract

Artificial intelligence (AI) has gained acceptance in the field of education. Nevertheless, existing research on AI in education, particularly in foreign language (FL) learning and teaching, is notably limited in scope and depth. In the present study, we addressed this research gap by investigating social and computer science students' perceptions of the integration and use of AI-based technologies in education, focusing specifically on foreign language teaching. Using an online questionnaire, we analysed factors such as students' field of study, gender differences, and the type of AI used. The questionnaire included statements categorised into thematic clusters, with responses measured on a five-point Likert scale. Statistical analysis, including chi-square tests and Cohen's d, revealed that individuals studying computer science, males, and supporters of generative AI are more likely to use AI tools for educational purposes. They perceive fewer barriers to the integration of AI into FL education. Social science students and women are less likely to use AI tools in FL education and express scepticism about their potential to improve academic outcomes. They tend to be more critical or cautious regarding the role of AI in FL education. They view AI as a valuable tool that enhances the learning experience but, at the same time, recognise the irreplaceable role of human teachers. The study highlights the need for targeted educational initiatives to address gender and disciplinary…

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  • Academic integrity enforcement emerged as a central concern, particularly regarding unauthorised AI use in assessments and the difficulty of detecting AI-generated content.

    “Academic integrity enforcement emerged as a central concern, particularly regarding unauthorised AI use in assessments and the difficulty of detecting AI-generated content.”

    From Six Institutional Intervention Areas to Support Ethical and Effective Student Use of Generative AI in Higher Education: A Narrative Review (2026) · cites this paper as Dolenc & Brumen, 2024

  • The literature increasingly recognises that effective AI use requires more than access; it demands skill, including prompt engineering, interpreting AI-generated results, and recognising limitations or biases.

    “The literature increasingly recognises that effective AI use requires more than access, it demands skill. Students must learn how to use AI tools confidently and competently, which includes understanding prompt engineering, interpreting AI-generated results, and recognising the limitations or biases inherent in these systems (Dolenc & Brumen, 2024; Haq et al., 2025; Mahrishi et al., 2024).”

    From Six Institutional Intervention Areas to Support Ethical and Effective Student Use of Generative AI in Higher Education: A Narrative Review (2026) · cites this paper as Dolenc & Brumen, 2024

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Authors
Dolenc, K., & Brumen, M.
Affiliations
University of Maribor (SI)
Corresponding author
Dolenc, Kosta
ORCID
Venue
Computers and Education: Artificial Intelligence
Publisher
Elsevier BV
Published
2024-12
Volume
7
Pages
100285
ISSN
2666-920X (ISSN-L)
DOI
10.1016/j.caeai.2024.100285
OpenAlex
W4401906348
Cited by
25
References
17
Citations by year
2026: 10 · 2025: 14 · 2024: 1
FWCI
9.43
Type
journal article
Language
en
Open access
Licence
Locations
  • Computers and Education Artificial Intelligence (publishedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Educational Technology and Pedagogy
  • Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
Keywords
artificial intelligence in education, foreign language teaching, student perceptions, generative AI, social sciences students, computer science students, gender differences, disciplinary differences, AI adoption barriers, teacher role, AI training programs, responsible AI use

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