Uji Validitas dan Reliabilitas Instrumen Ketergantungan Kecerdasan Buatan untuk Mahasiswa Calon Guru Matematika
DOI:
10.29303/jm.v8i3.13021Published:
2026-09-30Downloads
Abstract
The use of Artificial Intelligence (AI) in academic activities has increased significantly, creating the need for a valid and reliable instrument to measure students' dependence on Artificial Intelligence. This study aimed to examine the validity and reliability of an Artificial Intelligence dependence instrument administered to 89 prospective mathematics teachers. The study employed a quantitative descriptive approach. The research instrument was a questionnaire consisting of 20 items covering five aspects: usage, feelings, usefulness, ease of access, and dependence on Artificial Intelligence. The instrument was adapted from an existing questionnaire and modified to suit the context of prospective mathematics teachers. Item validity was analyzed using the Pearson Product–Moment correlation, while reliability was evaluated using Cronbach's Alpha. The results indicated that all questionnaire items were valid. The reliability analysis yielded a Cronbach's Alpha coefficient of 0.78, which falls into the high reliability category, indicating that the instrument has good internal consistency. Therefore, the Artificial Intelligence dependence instrument was found to be valid and reliable, making it suitable for measuring the level of dependence on Artificial Intelligence among prospective mathematics teachers.
Keywords:
artificial intelligence dependence instrument prospective mathematics teachers reliability validityReferences
Ahmad, A., Purwito, L., Listyaningrum, R. A., & Hidayat, R. (2025). Evaluating Students’ Artificial Intelligence Literacy: Development of an Assessment Instrument Based on Experiential Learning Elements. Indonesian Journal of Instruction, 6(3), 595-608.
Afrita, J. (2023). Peran artificial intelligence dalam meningkatkan efisiensi dan efektifitas sistem pendidikan. COMSERVA: Jurnal Penelitian Dan Pengabdian Masyarakat, 2(12), 3181-3187.
Ananta, E. P., & Kurniawan, R. (2026). Analisis Properti Psikometrik ChatGPT Usage Scale in Education dalam Konteks Bahasa Indonesia. Jurnal Psikologi Udayana, 13(1).
Arifin, Z. (2017). Kriteria instrumen dalam suatu penelitian. Jurnal Theorems (the original research of mathematics), 2(1), 28-36.
Arikunto, S. (2009). Dasar-dasar Evaluasi Pendidikan (edisi revisi).
Arikunto, S. (2021). Dasar-dasar evaluasi pendidikan (Edisi 3). Jakarta: Bumi Aksara.
Baharudin, B., Nety, N., Azis, A., Rahmatia, R., & Iriana, A. (2025). Pemanfaatan AI Sederhana Untuk Meningkatkan Kesiapan Mahasiswa FKIP dalam Pembelajaran Abad ke-21. Kamba Mpu: Jurnal Pengabdian Masyarakat, 20-25.
Carolus, A., Koch, M. J., Straka, S., Latoschik, M. E., & Wienrich, C. (2023). MAILS-Meta AI literacy scale: Development and testing of an AI literacy questionnaire based on well-founded competency models and psychological change-and meta-competencies. Computers in Human Behavior: Artificial Humans, 1(2), 100014.
Hairun, Y. (2020). Evaluasi dan penilaian dalam pembelajaran. Deepublish.
Hou, C., Zhu, G., Sudarshan, V., Lim, F. S., & Ong, Y. S. (2025). Measuring undergraduate students' reliance on Generative AI during problem-solving: Scale development and validation. Computers & Education, 234, 105329.
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and individual differences, 103, 102274.
Kshetri, N., Hughes, L., louise Slade, E., Jeyaraj, A., kumar Kar, A., Koohang, A., ... & Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642.
Morales-García, W. C., Sairitupa-Sanchez, L. Z., Morales-García, S. B., & Morales-García, M. (2024, March). Development and validation of a scale for dependence on artificial intelligence in university students. In Frontiers in Education (Vol. 9, p. 1323898). Frontiers Media SA.
Pemerintah Republik Indonesia. (2025). Peraturan Presiden Republik Indonesia Nomor 12 Tahun 2025 tentang Rencana Pembangunan Jangka Menengah Nasional Tahun 2025–2029. https://peraturan.bpk.go.id
Pingmuang, P., Koraneekij, P., & Khlaisang, J. (2026). Development and Validation of an AI Literacy Scale for Pre-Service Teachers in Thailand. Electronic Journal of e-Learning, 24(1), 1-18.
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart learning environments, 10(1), 15.
United Nations. (2015). Transforming our world: The 2030 agenda for sustainable development. https://sdgs.un.org/2030agenda
Zhang, H., Yang, Y., Zhang, Y., Qiu, B., & Yang, J. (2026). Generative AI dependency on programming among university students: a scale development and validation study. BMC psychology.
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Copyright (c) 2026 Sabrina Aprilia, Elisa Mutiara Fatmadewi, Indah Maulidya, Ahmad Taufik Hidayat, Nafa Nur Rakhima, Nuriana Rachmani Dewi

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