构造(python库)
数学教育
科学教育
定性研究
化学
心理学
计算机科学
社会学
社会科学
程序设计语言
作者
Morgan Balabanoff,Simreen Kaur,Jack Barbera,Alena Moon
标识
DOI:10.1080/09500693.2022.2055190
摘要
Across science disciplines, light is a common tool for measuring, characterizing, and catalysing molecules and molecular processes. Despite the ubiquity of light-based tools, little research has been done to investigate how students understand light and light–matter interactions (LMI). This topic is typically first introduced in first-year undergraduate chemistry courses where students initially encounter the quantum nature of light and matter. How students make sense of this content and transition from classical concepts to quantum concepts is relatively unknown. To gain further insight on how students develop quantum-level conceptions about light, we use a construct modelling approach. This approach is best suited to capture progressions in student understanding. In this study, we begin to model students' understanding of LMI by first developing a model for the nature of light. Two sets of qualitative interviews were conducted about the particulate nature of light and the wave nature of light. Analysis of interviews resulted in four construct maps, which can provide information to instructors and researchers about the variation in student understanding of the nature of light. Findings from this study have implications for how quantum chemistry is introduced at the postsecondary level.
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