Pengaruh intensitas penggunaan platform artificial intelligence terhadap motivasi belajar mahasiswa

Authors

  • Nurul Atiba Universitas Mataram
  • Edy Herianto Universitas Mataram
  • Basariah Basariah Universitas Mataram

DOI:

https://doi.org/10.24036/jecco.v6i1.965

Keywords:

artificial intelligence, learning motivation, civic education

Abstract

This study aims to investigate the influence of the intensity of using Artificial Intelligence (AI) platforms on the learning motivation of students in the Pancasila and Citizenship Education (PPKn) Study Program at the University of Mataram. Along with the rapid digital transformation in higher education, AI has become a cognitive support instrument that affects the psychological dynamics of students in learning. This study used a quantitative approach with the ex post facto method. The research population consisted of PPKn students from the class of 2022, with a sample size of 66 respondents determined through stratified proportional random sampling technique. Data were collected using a Likert scale questionnaire that had been tested for validity and reliability (Cronbach's Alpha for variable X = 0.896 and Y = 0.996). Data analysis techniques included simple linear regression and One-Way ANOVA. The results showed that the intensity of AI use had a positive and significant effect on student learning motivation (Sig. 0.000 < 0.05) with a regression coefficient of 0.296. The results of the One-Way ANOVA also showed significant differences in learning motivation between intensity groups (F = 5.603; Sig = 0.006). Post Hoc Tukey further testing revealed that a significant surge in motivation occurred when students moved from low to moderate use levels, but tended to stabilize from moderate to high levels. This study concludes that AI acts as a motivational catalyst through the ease of access to information and the enhancement of students' academic confidence in mastering complex materials.

References

Amayreh, A., Amnha, M. A. T., Magableh, I. K., Mahrouq, M. H., & Alfaiza, S. A. (2025). Exploring the impact of AI on employee self-competence performance key variables and outcomes. 1–24.

Amofa, B., Kamudyariwa, X. B., Araujo, F., Fernandes, P., & Osobajo, O. A. (2025). Navigating the Complexity of Generative Artificial Intelligence in Higher Education : A Systematic Literature Review. 1–22.

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? FAccT 2021 - Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. https://doi.org/10.1145/3442188.3445922

Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: the state of the field. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00392-8

Davar, N. F., & Dewan, M. A. A. (2025). AI Chatbots in Education : Challenges and Opportunities.

Ertel, W. (2017). Introduction of Artificial Intelligence. In Smart Systems for Industrial Applications. https://doi.org/10.1002/9781119762010.ch6

Ertel, W. (2024). Introduction to artificial intelligence. Springer Nature.

Hapsari, D. D., Ramadhani, G. Y., & Ikramullah, N. I. (2024). Literature Review : Pengaruh Artificial Intelligence ( Ai ) Terhadap Motivasi Belajar Peserta Didik. Jurnal Empati, 13(4), 313–324.

Herianto, E. (2014). E-Learning, implementasi teknologi di era belajar: Kajian pada mata kuliah kurikulum pkn di jurusan pips fkip universitas mataram. Jurnal Pendidikan dan Pembelajaran (Jpp), 20(1), 1–8.

Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European journal of education, 57(4), 542–570.

Imam Ghozali. (2021). Aplikasi Analisis Multivariate Dengan Program SPSS 26. In Badan Penerbit Universitas Diponegoro.

John W. Creswell. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th editio). SAGE Publications, Inc.

Johnnie Daniel. (2019). Preparing to Make Sampling Choices. SAGE Publications, Inc. https://doi.org/https://dx.doi.org/10.4135/9781452272047 Print

Keller, J. M. (1987). Development and use of the ARCS model of instructional design. Journal of instructional development, 10(3), 2–10.

Nelliraharti. (2024). Pengaruh Artificial Intelegence (AI) Terhadap Motivasi Belajar Mahasiswa. Journal of Education Science (JES), 10(1), 139–151.

Nilsson, N. J. (2010). The Quest for Artificial Intelligence: A History of Ideas and Achievements. Cambridge University.

Ormrod, J. E. (2020). Essentials of educational psychology (6th ed.). Pearson Merrill Prentice Hall Essex.

Peng, J., & Li, Y. (2025). Frontiers of Artificial Intelligence for Personalized Learning in Higher Education : A Systematic Review of Leading Articles. 1–32.

Pensyarah, L., & Tinggi, B. (2025). Digital Transformation in Accounting Education : Exploring the Influence of Lecturers ’ Behavioural Intentions and High-Context Culture. 74, 1–19.

Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of educational psychology, 82(1), 33.

Porayska-Pomsta, K. (2025). AI in Education as a methodology for enabling educational evidence-based practice.

Pratama, A. (2024). Pengaruh ChatGPT Terhadap Berpikir Kritis Mahasiswa Informatika Kelas D Angkatan 2023 Universitas Atma Jaya Yogyakarta. June. https://doi.org/10.13140/RG.2.2.14841.89443

Purba, Dany Bethcamp Lubis, Gabriel Bonar Sihombing Purba, & Juwita Simarmata. (2025). Pengaruh Penggunaan Teknologi AI ( Artificial Inteligence ) Terhadap Motivasi Belajar Mahasiswa Jurusan Pendidikan Teknik Elektro Unimed. Jurnal Pengabdian Masyarakat dan Riset Pendidikan, 3(3), 379–384. https://doi.org/10.31004/jerkin.v3i3.402

Riduwan. (2012). Skala Pengukuran Variabel-Variabel Penelitian (CET. 9). Alfabeta. https://inlislite.ipdn.ac.id/opac/detail-opac?id=15322

Sandu Siyoto & M. Ali. (2015). Dasar metodologi penelitian (Ayup (ed.)). Literasi Media Publishing.

Schunk, D. H., & Zimmerman, B. J. (2012). Motivation and self-regulated learning: Theory, research, and applications. Routledge.

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

Uno, H. B. (2011). Teori motivasi dan pengukurannya: Analisis di bidang pendidikan. Bumi Aksara.

Uno, H. B. (2016). Teori Motivasi Belajar dan Pengukurannya. In Junwinanto (Ed.), Jakarta: Bumi Aksara (Ed.1). Bumi Aksara. https://books.google.co.id/books?id=8o5_tQEACAAJ&printsec=frontcover&hl=id#v=onepage&q&f=false

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Published

2026-04-30

How to Cite

Atiba, N., Herianto, E., & Basariah, B. (2026). Pengaruh intensitas penggunaan platform artificial intelligence terhadap motivasi belajar mahasiswa. Journal of Education, Cultural and Politics , 6(1), 198–206. https://doi.org/10.24036/jecco.v6i1.965