Digital competence and strategic AI tool selection in higher education: Evidence from Indonesian university students
DOI:
https://doi.org/10.55573/JISED.118810Keywords:
Artificial Intelligence, AI Tool Usage, Student Preferences, AI Tool Selection, Institutional Support, AI Literacy, Higher EducationAbstract
The increasing integration of artificial intelligence (AI) tools into higher education has transformed students' academic learning practices. This study aims to examine students' AI tool usage patterns, preferences, academic purposes, selection strategies, and perceptions of institutional support and training needs. A cross-sectional survey was conducted among 231 purposively selected students from the Faculty of Tarbiyah and Teacher Training at Universitas Islam Negeri (UIN) Syarif Hidayatullah Jakarta, Indonesia, using a structured online Google Forms questionnaire administered from 4 to 10 October 2026 comprising closed-ended items and open-ended questions. Data were analysed using descriptive statistics, including frequencies, percentages, means, and standard deviations, while open-ended responses were examined through keyword-based thematic analysis. The findings revealed that ChatGPT was the most widely used AI tool (90.5%), followed by Google Gemini (72.3%) and Google Translate (52.4%). Most respondents (67.1%) used two or three AI tools for academic purposes. AI was primarily used for searching academic information (M = 3.49), generating examples and explanations (M = 3.44), and summarising learning materials (M = 3.41), while its use for research, data analysis, and programming was comparatively limited. Students reported moderate levels of AI tool-selection strategies (M = 3.50) and perceived institutional support (M = 3.38). However, the perceived need for AI training and institutional policies was relatively higher (M = 3.65), particularly regarding ethical AI use, verification of AI-generated information, and acknowledgement of AI assistance in academic work. Furthermore, only 36.8% of respondents had received formal AI training. The findings highlight the importance of strengthening institutional AI literacy initiatives, providing clear academic guidelines, and promoting responsible and purposeful AI use in higher education.
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Al-Moghrabi, K. G., & Al-Ghonmein, A. M. (2024). The role of chat generative pre-trained transformer in facilitating decision-making and the e-learning process in higher education. Bulletin of Electrical Engineering and Informatics, 13(3), 2058–2066. https://doi.org/10.11591/eei.v13i3.7237
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quiñonez, H. R., & Young, S. L. (2018). Best practices for developing and validating scales for health, social, and behavioral research: A primer. Frontiers in Public Health, 6, Article 149. https://doi.org/10.3389/fpubh.2018.00149
Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20, Article 38. https://doi.org/10.1186/s41239-023-00408-3
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20, Article 43. https://doi.org/10.1186/s41239-023-00411-8
Du, J., & Daniel, B. K. (2024). Transforming language education: A systematic review of AI-powered chatbots for English as a foreign language speaking practice. Computers and Education: Artificial Intelligence, 6, Article 100230. https://doi.org/10.1016/j.caeai.2024.100230
Huang, W., Hew, K. F., & Fryer, L. K. (2022). Chatbots for language learning—Are they really useful? A systematic review of chatbot-supported language learning. Journal of Computer Assisted Learning, 38(1), 237–257. https://doi.org/10.1111/jcal.12610
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Stadler, M., ... Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274
Kim, N.-Y., Kim, H.-S., & Cha, Y.-J. (2019). Future English learning: Chatbots and artificial intelligence. Multimedia-Assisted Language Learning, 22(3), 32–53. https://doi.org/10.15702/MALL.2019.22.3.32
Mageira, K., Pittou, D., Papasalouros, A., Kotis, K., Zangogianni, P., & Daradoumis, A. (2022). Educational AI chatbots for content and language integrated learning. Applied Sciences, 12(7), Article 3239. https://doi.org/10.3390/app12073239
Mardiana, H. (2026). Developing digital literacy and competence in Southeast Asia higher education: The role of institutional support and prior AI experience. Asian Education and Development Studies. Advance online publication. https://doi.org/10.1108/AEDS-09-2025-0457
Margono, H., Saud, M., & Falahat, M. (2024). Virtual tutor, digital natives and AI: Analyzing the impact of ChatGPT on academia in Indonesia. Social Sciences & Humanities Open, 10, Article 101069. https://doi.org/10.1016/j.ssaho.2024.101069
Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
Mizan, N. A., & Norman, H. (2024). Persepsi pelajar pra-universiti dalam menggunakan AI generatif: Kajian di universiti swasta Malaysia. Jurnal Pendidikan Bitara UPSI, 17(2), 138–149. https://doi.org/10.37134/bitara.vol17.2.12.2024
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, Article 100041. https://doi.org/10.1016/j.caeai.2021.100041
Noor, M. L. A. M., Isa, M. A., Sahrir, M. S., & Ghalib, M. F. M. (2026). Potentials of artificial intelligence in enhancing postgraduate research skills in sustainable language education: A systematic literature review. International Journal of Learning, Teaching and Educational Research, 25(9), 502–522. https://doi.org/10.26803/ijlter.25.9.20
Noor, M. L. A. M., Isa, M. A., Sahrir, M. S., Ghalib, M. F. M., & Aziz, N. F. A. (2026). Development and validation of an AI framework for enhancing postgraduate research skills in sustainable language education: A Fuzzy Delphi analysis. Intellectual Discourse, 34(3), 791–820.
Petrović, J., & Jovanović, M. (2021). The role of chatbots in foreign language learning: The present situation and the future outlook. In E. Pap (Ed.), Artificial intelligence: Theory and applications (pp. 313–330). Springer. https://doi.org/10.1007/978-3-030-72711-6_17
Pimentel, J. L. (2010). A note on the usage of Likert scaling for research data analysis. USM R&D Journal, 18(2), 109–112.
Sari, D. K., Supahar, S., Rosana, D., Dinata, P. A. C., & Istiqlal, M. (2025). Measuring artificial intelligence literacy: The perspective of Indonesian higher education students. Journal of Pedagogical Research, 9(2), 143–157. https://doi.org/10.33902/JPR.202531879
Singh, K., Agustine, E. C., Samasu, N. F., & Kipli, N. A. (2024). Exploring students’ perceptions of ChatGPT: A study of public university in Malaysia. International Journal of Research and Innovation in Social Science, 8(11), 1387–1397. https://doi.org/10.47772/IJRISS.2024.8110112
Tan, C. N. L., Tee, M., & Koay, K. Y. (2024). Discovering students’ continuous intentions to use ChatGPT in higher education: A tale of two theories. Asian Education and Development Studies, 13(4), 356–372. https://doi.org/10.1108/AEDS-04-2024-0096
Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach's alpha. International Journal of Medical Education, 2, 53–55. https://doi.org/10.5116/ijme.4dfb.8dfd
Teoh, K. B., & Tan, W. L. (2026). Policy alignment and trustworthy AI governance in higher education: A conceptual analysis of Malaysia’s reform agenda and ASEAN governance imperatives. Journal of Interdisciplinary Studies in Education, 15(4), 1–22. https://doi.org/10.32674/eqphhh11
Universiti Malaya. (2026, March 15). Universiti Malaya releases policy and guidelines on the use of artificial intelligence in teaching and learning. https://spm.um.edu.my/2026/03/15/universiti-malaya-releases-policy-and-guidelines-on-the-use-of-artificial-intelligence-in-teaching-and-learning/
Wang, T., Lund, B. D., Marengo, A., Pagano, A., Mannuru, N. R., Teel, Z. A., & Pange, J. (2023). Exploring the potential impact of artificial intelligence (AI) on international students in higher education: Generative AI, chatbots, analytics, and international student success. Applied Sciences, 13(11), Article 6716. https://doi.org/10.3390/app13116716
Zainuddin, N., Suhaimi, N. A., Jaffar, M. N., Norwawi, N. M., Sahrir, M. S., Wan Daud, W. A. A., & Abdul Ghani, M. T. (2024). Responsible and ethical use of artificial intelligence in language education: A systematic review. Forum for Linguistic Studies, 6(5), 316–325. https://doi.org/10.30564/fls.v6i5.7092
Zhang, Z., & Huang, X. (2024). The impact of chatbots based on large language models on second language vocabulary acquisition. Heliyon, 10(3), Article e25370. https://doi.org/10.1016/j.heliyon.2024.e25370
