科学教育
课程
背景(考古学)
社会科学教育
科学的本质
数学教育
社会学
社会科学概论
教育学
心理学
生物
古生物学
作者
Melike Akbayrak,Ebru Kaya
标识
DOI:10.1080/09500693.2020.1790054
摘要
This study is based on the Reconceptualised Family Resemblance Approach to Nature of Science (Kaya & Erduran, 2016 Kaya, E., & Erduran, S. (2016). From FRA to RFN, or how the Family Resemblance Approach can be transformed for science curriculum analysis on nature of science. Science & Education, 25(1115), 9–10. 1133 [Google Scholar]), which explains science as a cognitive, epistemic, and social-institutional system. A content analysis of Turkish science curricula shows that the social context of science is underemphasised (Kaya & Erduran, 2016 Kaya, E., & Erduran, S. (2016). From FRA to RFN, or how the Family Resemblance Approach can be transformed for science curriculum analysis on nature of science. Science & Education, 25(1115), 9–10. 1133 [Google Scholar] ). Therefore, this study investigated the impact of teaching science as a social-institutional system on fifth-grade students' understanding of the social dimension of science. Using a quasi-experimental research design, Social-Institutional Questionnaire (SIQ) was administered to both the experimental group (n=19) and control group (n = 23) as a pre-and post-test. Throughout the intervention, the experimental group was exposed to science lessons enriched with social-institutional aspects of science; the control group was taught with traditionally-designed science lessons on a unit 'The Earth, Sun and Moon'. The results of ANCOVA showed a statistically significant difference between the groups in favour of the experimental group. Interviews and worksheets were used to support the findings. It was found that integrating social-institutional aspects of science into science lessons enhanced students' understanding of the social-institutional aspects of science. This study contributes to the literature on NOS in science education and provides science teachers a resource for teaching social-institutional aspects of science.
科研通智能强力驱动
Strongly Powered by AbleSci AI