Elementary School Students’ Ecosystem Scientific Argumentation Based on the Rule-Space Model: Pathways and Remediation
摘要
The importance of scientific argumentation is reflected not only in the depth of knowledge construction but, more importantly, in its role in fostering students’ scientific thinking. Existing domain-specific research on learning progressions in scientific argumentation has largely focused on selected components (e.g., claim and explanation) and has primarily targeted secondary school students. Furthermore, inconsistent definitions of the constituent elements of scientific argumentation across studies have led to fragmented models of learning progression. This study employed the Rule-Space Model to investigate the developmental pathways of elementary school students’ scientific argumentation in the ecosystem domain. First, the study developed an attribute hierarchy model of ecosystem scientific argumentation consisting of five attributes: Expressing a Claim, Providing Evidence, Simple Reasoning, Complex Reasoning, and Rebuttal. Based on this model, eight ideal attribute mastery patterns and three potential learning progression pathways were generated. Second, an Assessment Tool for Measuring Students’ Learning Progression in Scientific Argumentation in the Context of Ecosystems (ATMSLPSA) was developed. Following pilot testing with 101 students and subsequent refinement, the final instrument was administered to 320 sixth-grade students in China, yielding 299 valid responses. The results supported the effectiveness of the three proposed learning progression pathways. Based on these pathways, this study classified elementary school students’ learning progression in ecosystem scientific argumentation into five levels. Overall, students’ performance in scientific argumentation was concentrated primarily at Level 2, indicating that most students had developed the ability to make preliminary evidence-based inferences but still exhibited weaknesses in complex reasoning and rebuttal. Third, individual diagnostic reports on ecosystem scientific argumentation were generated from the response data, thereby facilitating inferences about potential subsequent developmental pathways and providing a basis for targeted instructional intervention and remediation.