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A Hierarchical Linear Modeling Approach to Understanding the Role of Ethnicity and Socioeconomic Status on Precollege Engineering Conceptions Research to Practice

机译:一种理解民族和社会经济地位对练习练习预制工程概念研究的作用的分层线性建模方法

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Traditional precollege formal education includes state and federal mandated science and mathematics content. Most recently standards also include engineering content to support initiatives that prepare more of the American population for the engineering challenges of the future. This study focused on a precollege engineering education intervention. Potential interactions between student and school level factors and students' pre-test achievement were explored using a multilevel modeling data analysis approach (i.e. investigating students within schools). Findings suggest that the statistically significant predictors of the students' pre-test scores are school socioeconomic status and ethnicity. Students who attended a school with a higher proportion of students on free and reduced lunch (FRL) - where FRL is used as a measure of socio-economic status - on average have lower scores than those who attend schools with a lower proportion of FRL receiving students. The second finding is that on average, African American and Hispanic students earn fewer points on the pre-test than do students belonging to other ethnic groups. The findings further suggest that family and community knowledge can influence student knowledge and test scores. As engineering education researchers and practitioners, we must apply these insights to the ways that we engage with diverse students and to the design of our curricula.
机译:传统的前冰上正规教育包括州和联邦授权科学和数学内容。最近标准还包括工程内容,以支持为未来的工程挑战制备更多美国人口的举措。本研究专注于前冰上的工程教育干预。使用多级建模数据分析方法(即学校内的学生)探讨了学生和学校级别因素和学生的预审绩效的潜在相互作用。调查结果表明,学生的预测分数的统计上重要预测因子是学校社会经济地位和种族。在自由和减少午餐(FRL)的学生中出席学校的学生 - 将FRL被用作社会经济地位的衡量标准 - 平均水平较低的分数比上学比例较低的FRL接收学生们。第二个发现是,平均而言,非洲裔美国和西班牙裔学生的预先测试比属于其他族裔的学生赚取更少的点。调查结果进一步表明家庭和社区知识可以影响学生的知识和测试分数。作为工程教育研究人员和从业者,我们必须对我们与各种学生和课程设计进行互动的方式应用这些见解。

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