Profile of Computational Thinking Skills of Pre-Service Chemistry Teachers

Abstract

This study aims to analyze the computational thinking (CT) skills of pre-service chemistry teachers using a set of twelve test items adapted from the international CT Bebras Challenge. The items represent three difficulty levels: easy, medium, and hard. The CT components assessed include algorithmic thinking, abstraction, and pattern recognition. A descriptive quantitative method was employed, involving students from a chemistry teacher education program. The responses were scored and analyzed using descriptive statistics to identify trends in students’ CT performance across components and difficulty levels. The results show varied levels of proficiency, with higher performance in pattern recognition tasks and lower performance in algorithmic thinking. These findings highlight the importance of embedding CT skill development in chemistry education and teacher training curricula.