ARTIFICIAL INTELLIGENCE AMONG PRE-SERVICE SCIENCE TEACHERS: PREPAREDNESS, PEDAGOGICAL USAGE AND IMPLEMENTATION CHALLENGES

Abstract

Pre-service science teachers are gradually adopting Artificial Intelligence (AI) as a transformative tool for effective teaching and learning. However, the issue of preparedness, pedagogical usage, and implementation challenges continue to be sources of concern. This study examined these concerns and their implications for teaching and learning. The study adopted a descriptive survey research design involving a proportionate stratified random sampling technique of 160 participants. Data were collected using a validated instrument titled "AI Integration Preparedness, Pedagogical Usage and Implementation Challenges (AI-PPUICQ). Preparedness ($\alpha = 0.93$), Pedagogical Usage ($\alpha = 0.91$) and challenges ($\alpha = 0.76$), measured on a 4-point Likert scale and subjected to descriptive (percentages and means) and regression analysis. Results showed that respondents reported moderate levels of AI preparedness, while their pedagogical usage was high. The most prevalent challenges were resources and infrastructure with a total mean score of 2.85; and institutional support was the least challenge they encounter with a mean score of 2.43. Furthermore, results showed that the influence of AI preparedness on pedagogical use was statistically significant ($\beta = .505, p < .001$). This paper highlights the importance of supporting pre-service science teachers' AI literacy through enhancing their capacity for pedagogical integration, minimizing obstacles, and encouraging responsible, creative classroom practice. These results underscore the importance of specific training, infrastructure, and supportive policies on the integration of AI in science education.