Characterization of mechanistic reasoning in science teacher candidates on some science topics

This study aims to describe the mechanistic reasoning skills of science teacher candidates in a multidimensional framework by examining their written explanations on the topics of "buoyancy" (physics), "boiling point" (chemistry), and "digestive system" (biology). The "explanation–reasoning" competency, which is among the 21st-century skills emphasized by global education policies, is considered one of the fundamental components of science literacy. However, there is no study in Turkey that systematically investigates this competency in the context of teacher candidates. The research presents the explanatory components (entities, properties, activities, organization, initiation) of the mechanistic reasoning model proposed by Russ et all. (2008) and the reasoning levels defined by Moreira et al. (2019) (descriptive, relational, simple cause-effect, developing mechanistic) to present an interdisciplinary analysis. The study was conducted using a qualitative content analysis-based coding process on written texts collected from 2nd to 4th-year students enrolled in the Science Education program at Fırat University's Faculty of Education during the 2023-2025 academic years who volunteered for the research. In this context, (i) which mechanistic components candidates used for each topic, (ii) at which levels of reasoning they organized these components, and (iii) interdisciplinary similarities and differences were mapped in detail. The research findings show that teacher candidates' explanations are predominantly stuck at the relational and simple cause-and-effect level; they only give limited space to developing mechanistic explanations that include activity and organization components. This situation reveals that candidates have difficulty examining complex causal mechanisms in science subjects from a holistic perspective, thus highlighting the need to support mechanistic thinking with planned teaching activities. The results of the study offer concrete recommendations for (i) including explanation-focused writing and modeling activities in teacher training programs, (ii) designing interdisciplinary tasks that emphasize reciprocal-dynamic causality, and (iii) implementing individualized feedback loops. Thus, this study not only fills a gap in the local literature but also provides empirical support for pedagogical designs aimed at developing mechanistic reasoning in science education. Key Words: Science Education, Mechanistic Reasoning, Physics, Chemistry, Biology