PENGARUH EFIKASI DIRI AI DAN PENGGUNAAN CHATGPT TERHADAP PERSEPSI AI: PERAN MEDIASI LITERASI AI

Authors

  • Citra Damayanti Universitas Sebelas Maret, Indonesia
  • Silky Roudhotus Sa’adah Universitas Sebelas Maret, Indonesia

DOI:

https://doi.org/10.33603/ejpe.v14i2.12544

Abstract

The rapid development of artificial intelligence (AI) has increased the use of ChatGPT in higher education, yet frequent use does not necessarily lead to positive perceptions of AI. This study examines the effects of AI self-efficacy and ChatGPT use on students’ perceptions of AI, with AI literacy as a mediating variable. A quantitative explanatory research design was employed. The population consisted of 479 Economic Education students at Universitas Sebelas Maret from the 2022–2025 cohorts. Using purposive sampling, 100 students who had used ChatGPT for academic purposes were selected as respondents. Data were collected through a four-point Likert-scale questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that AI self-efficacy has positive and significant effects on AI perception and AI literacy. ChatGPT use has a positive and significant effect on AI literacy but does not significantly affect AI perception. AI literacy positively and significantly affects AI perception. Furthermore, AI literacy partially mediates the effect of AI self-efficacy on AI perception but does not mediate the effect of ChatGPT use on AI perception. These findings underscore the importance of strengthening AI self-efficacy and AI literacy to support more informed perceptions of AI in learning.

Keywords: AI self-efficacy, ChatGPT usage, AI perception, AI literacy.

References

Alessandro, G., Dimitri, O., Cristina, B., & Anna, M. (2025). The Emotional Impact of Generative AI: Negative Emotions and Perception of Threat. Behaviour & Information Technology, 44(4), 1-48, https://doi.org/10.1080/0144929X.2024.2333933

Albolle-Okoyeagu, C.J., Ezenkwu, C.P., Ibeke, E., Onoja, O, J., & Ezeonwumelu, V.U. (2026). Engineering students and AI in education: a TAM based study of perceptions, acceptance, and barriers to adoption. Cogent Education, 13(1), 1-22. https://doi.org/10.1080/2331186X.2026.2614148

Ammari, T., Chen, M., Zaman, S. M. M., & Garimella, K. (2026). Learning to Live with AI: How Students Develop AI Literacy Through Naturalistic ChatGPT Interaction, Computer Science, 1-43 http://arxiv.org/abs/2601.20749

Berdida, D. J. E., Grande, R. A. N., Serag, R. M., & Abd Elmaksoud, D. M. F. (2026). Nursing students’ artificial intelligence (AI) literacy, AI self-efficacy and AI self-competency: A cross-sectional design and structural equation model analysis. Nurse Education in Practice, 90, 1-10. https://doi.org/10.1016/j.nepr.2025.104673

Dogaru, M., Pisică, O., Popa, C. Ștefan, Răgman, A. A., & Tololoi, I. R. (2025). The perceived impact of artificial intelligence on academic learning. Frontiers in Artificial Intelligence, 8, 1-13. https://doi.org/10.3389/frai.2025.1611183

Habibi, A., Muhaimin, M., Danibao, B. K., Wibowo, Y. G., Wahyuni, S., & Octavia, A. (2023). ChatGPT in higher education learning: Acceptance and use. Computers and Education: Artificial Intelligence, 5, 100190. https://doi.org/10.1016/j.caeai.2023.100190

Hair, J.F., Hult, G.T., Ringle, C.M., Sarsedt, M., Danks, N.P., Ray, S. (2021). Classroom Companion: Business Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R AAWorkbook. Springer Nature Switerland AG.

Ho, N. T. T., & Le, H. Van. (2026). Empowered by AI: exploring the link between literacy, self-efficacy, and career expectations. Acta Psychologica, 264, 1-16. https://doi.org/10.1016/j.actpsy.2026.106408

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. In Learning and Individual Differences, 103, 1-9. https://doi.org/10.1016/j.lindif.2023.102274

Meeker, M., Simons, J., Chae, D., & Krey, A. (2025). Trends—Artificial intelligence. BOND.

Ravšelj, D., Keržič, D., Tomaževič, N., Umek, L., Brezovar, N., Iahad, N. A., et al. (2025). Higher education students’ perceptions of ChatGPT: A global study of early reactions. PLoS ONE, 20(2), 1-53. https://doi.org/10.1371/journal.pone.0315011

Sallam, M., Elsayed, W., Al-Shorbagy, M., Barakat, M., El Khatib, S., Ghach, W., et al. (2024). ChatGPT usage and attitudes are driven by perceptions of usefulness, ease of use, risks, and psycho-social impact: a study among university students in the UAE. Frontiers in Education, 9, 1-15. https://doi.org/10.3389/feduc.2024.1414758

Schunk, D. H., & DiBenedetto, M. K. (2020). Motivation and social cognitive theory. Contemporary Educational Psychology, 60, 1-10. https://doi.org/10.1016/j.cedpsych.2019.101832

Soylu, M., Lee, J., Hung, J.-T., Zhang Cui, C., & Joyner, D. A. (2025.). AI Literacy as a Key Driver of User Experience in AI-Powered Assessment: Insights from Socratic Mind. Interactive Learning Environments, 34(5), 1-40. https://doi.org/10.1080/10494820.2025.2564739

Sugiyono. (2019). Metode Penelitian Kuantitatif, Kualiatif dan R&D. Alfabeta.

Wang, Y. Y., & Chuang, Y. W. (2024). Artificial intelligence self-efficacy: Scale development and validation. Education and Information Technologies, 29(4), 4785–4808. https://doi.org/10.1007/s10639-023-12015-w

Zhang, G., & Yu, T. (2025). Association between Generative AI self-efficacy and Generative AI acceptance: The mediating role of Generative AI trust and the moderating role of Generative AI risk perception. Acta Psychologica, 261, 1-8.https://doi.org/10.1016/j.actpsy.2025.105791

Zhao, Z., An, Q., & Liu, J. (2025). Exploring AI tool adoption in higher education: evidence from a PLS-SEM model integrating multimodal literacy, self-efficacy, and university support. Frontiers in Psychology, 16, 1-14. https://doi.org/10.3389/fpsyg.2025.1619391

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Published

2026-09-01

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