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Understanding pre-service teachers’ perceptions is essential as AI models such as ChatGPT, Claude, and Gemini gain attention in science education. This study developed a valid, trustworthy instrument to assess pre-service science teachers’ opinions in science-related educational settings. 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Ishmuradova 1*  \n 0000-0002-8191-1644  \nSergei P. Zhdanov 2  \n 0000-0002-1330-8165  \nSergey V. Kondrashev 3  \n 0000-0002-6547-865X  \nNatalya S. Erokhova 4  \n 0000-0002-8061-8112  \nElena E. Grishnova 5  \n 0000-0003-2080-3284  \nNonna Yu. Volosova 6  \n 0000-0003-3254-948X  \n1 Kazan (Volga region) Federal University, Naberezhnye Chelny Institute, Naberezhnye Chelny, RUSSIA  \n2 Department of Philosophy, Political Science, Sociology named after G.S. Arefieva, National Research University «Moscow Power Engineering Institute», Moscow, RUSSIA  \n3 I. M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, RUSSIA  \n4 Peoples’ Friendship University of Russia (RUDN University), Moscow, RUSSIA  \n5 Bauman Moscow State Technical University, Moscow, RUSSIA  \n6 Orenburg State University, Orenburg, RUSSIA  \n* Corresponding author: [izida-89@mail. ru](izida-89@mail. ru)  \nCitation: Ishmuradova, I. I., Zhdanov, S. P., Kondrashev, S. V., Erokhova, N. S., Grishnova, E. E., & Volosova, N. Y. (2025) . Preservice science teachers’ perception on using generative artificial intelligence in science education. Contemporary Educational Technology, 17(3), ep579. [https://doi.org/10.30935/cedtech/16207](https://doi.org/10.30935/cedtech/16207)  \nARTICLE INFO ABSTRACT  \nReceived: 3 Oct 2024  \nAccepted: 19 Mar 2025  \nThe development of generative artificial intelligence (AI) has started a conversation on its possible uses and inherent difficulties in the field of education. It becomes essential to understand the perceptions of pre-service teachers about the integration of this technology into teaching practices as AI models including ChatGPT, Claude, and Gemini acquire popularity. This investigation sought to create a valid and trustworthy instrument for evaluating pre-service science teachers’ opinions on the implementation of generative AI in educational settings related to science. This work was undertaken within the faculty of education at Kazan Federal University. The total number of participants is 401 undergraduate students. The process of scale development encompassed expert evaluation for content validity, exploratory factor analysis, confirmatory factor analysis, and assessments of reliability. The resultant scale consisted of four dimensions: optimism and utility of AI in science education, readiness and openness to AI integration, AI’s role in inclusivity and engagement, and concerns and skepticism about AI in science education. The scale demonstrated robust psychometric properties, evidenced by elevated reliability coefficients. Cluster analysis unveiled distinct profiles of pre-service teachers based on their responses, encompassing a spectrum from enthusiastic participants to skeptical disengaged individuals. This study provides a comprehensive instrument for evaluating preservice teachers’ perceptions, thereby informing teacher education programs and professional development initiatives regarding the responsible integration of AI. Recommendations entail the validation of the scale across varied contexts, the exploration of longitudinal changes, and the investigation of subject-specific applications of generative AI in science education.  \n\n| Keywords: generative artificial intelligence, science education, scale development, pre-service teacher’s perceptions\u003Cbr>INTRODUCTION |\n| --- |\n| The rapid evolution of generative artificial intelligence (AI) has sparked discussions about their applications and repercussions, as well as new paths in education. Models such as ChatGPT, Gemini, and Claude illustrate generative AI, a class of strong deep learning systems able to produce human-like material across various modalities (Michel-Villarreal et al., 2023; Su & Yang, 2023) . These AI systems have a","cbCairkRUUS0V3F8","https://ap.wps.com/l/cbCairkRUUS0V3F8","pdf",413445,18,"English","# ARTICLE INFO\n## Received and Accepted\n# ABSTRACT\n## Study purpose and context\n## Instrument development and dimensions\n## Psychometric evaluation and findings\n# INTRODUCTION\n## Generative AI in education\n## Challenges and need for AI literacy\n## Gap in scale research for science education","[{\"question\":\"What additional analysis was conducted to understand teacher profiles?\",\"answer\":\"Cluster analysis identified distinct profiles ranging from enthusiastic participants to skeptical disengaged individuals.\"}]","Pre-service science teachers’ perception on using generative artificial intelligence in science education - Research Article | PDF",1792090784,45]