9. sınıf öğrencilerinin, statik veya dinamik çoklu gösterimlerle desteklenen öğrenme ortamlarında gaz davranışına ilişkin anlamalarının incelenmesi

In this study, students' alternative conceptions related to gas behavior and the effects of two instructional interventions - namely inquiry instruction with static particulate representations (ISR) and inquiry instruction with dynamic particulate representations (IDR) - on students' conceptual understanding of gas behavior were examined. The research was conducted in two Grade 9 classes at a public high school located in Istanbul, including a total of 64 students, with 30 students in the ISR group and 34 students in the IDR group. The researcher co-taught both classes alongside their regular classroom teachers, ensuring that all students experienced the same instructional activities in an identical sequence and level of depth; the only distinction lay in the mode of representations provided - static for the ISR group and dynamic for the IDR group. Data were collected through the Two-Tier Gases Concept Test (TGCT) and interviews. The data were thoroughly coded and analyzed using both qualitative and quantitative methods. Based on the data analysis, seven categories of conceptual understanding of gas behavior were identified. The results showed that both groups held alternative conceptions before the instruction, and while the frequency of these conceptions changed following the intervention, some persisted. The sign test results indicated that students in both the ISR and IDR groups demonstrated a statistically significant improvement in their types of conceptual understanding from pretest to posttest (p < .001). However, the IDR group exhibited more substantial gains compared to the ISR group. Similarly, the independent samples t-test revealed that the IDR group achieved significantly greater progress than the ISR group, t(62) = -2.35, p < .022, suggesting that the inclusion of dynamic visualizations may enhance students' conceptual understanding of gas behavior more effectively than static representations.