谷歌浏览器插件
订阅小程序
在清言上使用

Mixed-methods Exploration of Students’ Written Belonging Explanations from General Chemistry at a Selective Institution

Chemistry Education Research and Practice(2023)

引用 2|浏览7
暂无评分
摘要
This exploratory, mixed-methods study examines first-year general chemistry students' written responses on a belonging survey. Responses were thematically analyzed to identify students’ sources of belonging, which may help instructors choose effective strategies for enhancing belonging during the transition into college. Qualitative analysis generated a codebook containing 21 codes from 6 categories: Course Attributes, Interest, Perceptions, Social, Student Attributes, and Value. The qualitative coding data were transformed into quantitative frequency data, allowing identification of the most frequent themes across all participants on each of four surveys: early- and late-semester General Chemistry 1 and 2. Additional analyses explored how belonging explanations varied based on student characteristics that might influence their experience of this large introductory STEM course at a selective, high-income, predominantly White institution. Unique sources of belonging were expected to emerge for groups marginalized in STEM (i.e., Black and Hispanic students, women) and groups who might feel discouraged by a selective institutional and course culture (i.e., students with no credit-bearing AP scores, low course grades, or high belonging uncertainty). Results indicate the importance of interest for all participants' course-level belonging. Students' career goals, perceptions of the course content, and social dynamics with peers also proved universally influential. Some patterns were especially pronounced for marginalized or discouraged groups, who were disproportionately likely to discuss social comparisons and interactions, self-evaluate, and describe the utility-value of the course. These groups were also less likely to express positive cognitive and affective engagement in the course. Implications for supporting student belonging throughout the course sequence are discussed.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要