Generative AI Use in Indonesian Language Learning: A Descriptive Survey of University Students

Despite considerable research attention to generative artificial intelligence (GenAI) in higher education, empirical evidence on its use in Indonesian language courses remains limited, particularly studies integrating usage, perceptions, opportunities, challenges, AI literacy, and ethics. This study aimed to describe these six dimensions among first-year university students. A quantitative descriptive survey involved 69 students from two parallel classes. Data were collected using a 30-item questionnaire (Cronbach’s α = .752–.873) and analyzed using descriptive statistics, categorical interpretation, and supplementary nonparametric comparisons. The findings showed that 87.0% of students had used GenAI, primarily Gemini and ChatGPT. Perceptions (M = 3.79), opportunities (M = 3.70), and ethical awareness (M = 3.82) were high, whereas challenges (M = 3.37), AI literacy (M = 3.27), and usage intensity (M = 2.88) were moderate. Users scored higher than non-users on perceptions, opportunities, and AI literacy; however, among users, AI literacy was not associated with frequency or duration of use. These findings suggest that students’ acceptance of GenAI exceeds their AI literacy, identifying a potential acceptance–competence gap in GenAI adoption. The study contributes a conceptual perspective on this gap and highlights the need for lecturers and institutions to integrate structured AI literacy and ethics instruction into Indonesian language courses. Further research should examine this gap using larger samples and performance-based measures.

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Publication Details

Journal
International Journal of Humanities Education and Social Sciences
Published
2026-11-06
DOI
https://doi.org/10.58578/ijhess.v4i3.12541
Primary Topic
Artificial Intelligence in Education
Type
article
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Generative AI Use in Indonesian Language Learning: A Descriptive Survey of University Students

Jafar
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International Journal of Humanities Education and Social Sciences
Artificial Intelligence in Education
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Generative AI Use in Indonesian Language Learning: A Descriptive Survey of University Students

Jafar
article en

Abstract

Despite considerable research attention to generative artificial intelligence (GenAI) in higher education, empirical evidence on its use in Indonesian language courses remains limited, particularly studies integrating usage, perceptions, opportunities, challenges, AI literacy, and ethics. This study aimed to describe these six dimensions among first-year university students. A quantitative descriptive survey involved 69 students from two parallel classes. Data were collected using a 30-item questionnaire (Cronbach’s α = .752–.873) and analyzed using descriptive statistics, categorical interpretation, and supplementary nonparametric comparisons. The findings showed that 87.0% of students had used GenAI, primarily Gemini and ChatGPT. Perceptions (M = 3.79), opportunities (M = 3.70), and ethical awareness (M = 3.82) were high, whereas challenges (M = 3.37), AI literacy (M = 3.27), and usage intensity (M = 2.88) were moderate. Users scored higher than non-users on perceptions, opportunities, and AI literacy; however, among users, AI literacy was not associated with frequency or duration of use. These findings suggest that students’ acceptance of GenAI exceeds their AI literacy, identifying a potential acceptance–competence gap in GenAI adoption. The study contributes a conceptual perspective on this gap and highlights the need for lecturers and institutions to integrate structured AI literacy and ethics instruction into Indonesian language courses. Further research should examine this gap using larger samples and performance-based measures.

International Journal of Humanities Education and Social SciencesVol. 4(3)
Quality education
Openalex Percentile: Top 10%
Artificial Intelligence in Education
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Generative AI Use in Indonesian Language Learning: A Descriptive Survey of University Students — Jafar · International Journal of Humanities Education and Social Sciences (2026) | TGRS Research Map | TGRS