Pre-service science teachers’ perception on using generative artificial intelligence in science education

Abstract

The 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 pre-service 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.