A Gap Analysis of Noncognitive Constructs in Evaluation Instruments Designed for Computing Education
A Gap Analysis of Noncognitive Constructs in Evaluation Instruments Designed for Computing Education
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DOI：
10.1145/3287324.3287362
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发表时间：
2019-02
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影响因子：
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通讯作者：
Monica Mcgill;Adrienne Decker;Tom Mcklin;K. Haynie
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文献类型：
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作者：
Monica Mcgill;Adrienne Decker;Tom Mcklin;K. Haynie
越来越多的证据表明，非认知因素对学业成就和学习有着深刻的影响。在这项研究中，我们分析了一组31个评估工具，旨在测量非认知结构（例如，自我效能、信心、动机）。使用Lee和Shute框架，我们将工具中发现的115个独特结构中的每一个分配到四个组件（学生参与，学习策略，学校氛围，社会家庭影响）及其子组件中的一个，以确定哪些结构最常被测量。我们发现，大多数结构的目的是衡量学生参与（情感和认知）和学校气氛（教师变量）。测量学习策略和社会家庭影响的结构（例如，家庭作业策略、同伴影响）发生最少。这项研究可能会进一步讨论哪些非认知因素是/目前没有被测量的计算教育界。
A growing body of evidence indicates that there is a deep effect of noncognitive factors on academic achievement and learning. In this study, we analyzed a set of 31 evaluation instruments designed to measure noncognitive constructs (e.g., self-efficacy, confidence, motivation) within computing education. Using the Lee and Shute framework, we assigned each of the 115 unique constructs found in the instruments into one of the four components (Student Engagement, Learning Strategies, School Climate, Social-familial Influences) and their subcomponents to determine which constructs are most frequently measured. We found that the majority of constructs were designed to measure Student Engagement (Affect and Cognition) and School Climate (Teacher Variables). Constructs measuring Learning Strategies and Social-Familial Influences (e.g., homework strategies, peer influences) occur the least. This study may enable further discussions of what noncognitive factors are/are not currently being measured within the computing education community.