Indonesian preservice teachers’ attitudes toward using ChatGPT: A structural equation model

Suprapto N. Hidaayatullaah H.N. Arymbekov B. Hakim S.R. Yulkifli
2025 Malque Publishing

Multidisciplinary Science Journal
2025 #7 Issue 7

This study investigates 232 preservice physics teachers attitudes toward using ChatGPT, an artificial intelligence-based conversational agent, in educational settings. With the increasing integration of technology in education, understanding preservice teachers perceptions of AI-driven tools is crucial for effective implementation. The research employs Partial Least Squares-Structural Equation Modeling (PLS-SEM) to analyze preservice teachers attitudes, including evaluating and checking, instructional design, multiple information, problem-solving, and time efficiency. The findings provide valuable insights into the validity and reliability of the measurement model and shed light on the structural relationships among the constructs under investigation. These insights have implications for theory and practice in educational research and instructional design. The implications for teacher education programs and the future integration of AI tools in pedagogical practices are also discussed.

ChatGPT , preservice teachers , structural equation modeling (SEM)

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Universitas Negeri Surabaya, Surabaya, Indonesia
Al-Farabi Kazakh National University, Satbayev University, Kazakhstan
Universitas Negeri Yogyakarta, Sleman, Indonesia
Universitas Negeri Padang, Padang, Indonesia

Universitas Negeri Surabaya
Al-Farabi Kazakh National University
Universitas Negeri Yogyakarta
Universitas Negeri Padang

10 лет помогаем публиковать статьи Международный издатель

Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026