Person-centered analyses in quantitative studies about broadening participation for Black engineering and computer science students

IF 3.9 2区 工程技术 Q1 EDUCATION & EDUCATIONAL RESEARCH Journal of Engineering Education Pub Date : 2023-05-22 DOI:10.1002/jee.20530
David Reeping, Walter Lee, Jeremi London
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Abstract

Background

There have been calls to shift how engineering education researchers investigate the experiences of engineering students from racially minoritized groups. These conversations have primarily involved qualitative researchers, but an echo of equal magnitude from quantitative inquiry has been largely absent.

Purpose

This paper examines the data analysis practices used in quantitative engineering education research related to broadening participation. We highlight practical issues and promising practices focused on “racial difference” during analysis.

Scope/Method

We conducted a systematic literature review of methods employed by quantitative studies related to Black students participating in engineering and computer science at the undergraduate level. Person-centered analyses and variable-centered analyses, coined by Jack Block, were used as our categorization framework, backdropped with the principles of QuantCrit.

Results

Forty-nine studies qualified for review. Although each article involved some variable-centered analysis, we found strategies authors used that aligned and did not align with person-centered analyses, including forming groups based on participant attitudes and using race as a variable, respectively. We highlight person-centered approaches as a tangible step for authors to engage meaningfully with QuantCrit in their data analysis decision-making.

Conclusions

Our findings highlight four areas of consideration for advancing quantitative data analysis in engineering education: operationalizing race and racism, sample sizes and data binning, claims with race as a variable, and promoting descriptive studies. We contend that engaging in deeper thought with these four areas in quantitative inquiry can help researchers engage with the difficult choices inherent to quantitative analyses.

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关于扩大黑人工程和计算机科学学生参与度的定量研究中的人本分析
背景有人呼吁改变工程教育研究人员调查少数种族群体工程学生经历的方式。这些对话主要涉及定性研究人员,但在很大程度上没有定量调查的同等规模的回应。目的本文探讨了与扩大参与相关的定量工程教育研究中使用的数据分析实践。在分析过程中,我们强调了关注“种族差异”的实际问题和有希望的做法。范围/方法我们对与黑人学生在本科阶段参与工程和计算机科学相关的定量研究所采用的方法进行了系统的文献综述。杰克·布洛克提出的以人为中心的分析和以变量为中心的分析作为我们的分类框架,并以QuantCrit的原理为背景。结果49项研究符合审查条件。尽管每篇文章都涉及一些以变量为中心的分析,但我们发现作者使用的策略与以人为中心的分析一致和不一致,包括分别根据参与者的态度组建小组和将种族作为变量。我们强调以人为中心的方法是作者在数据分析决策中有意义地参与QuantCrit的一个切实步骤。结论我们的研究结果强调了在工程教育中推进定量数据分析需要考虑的四个领域:操作种族和种族主义、样本量和数据装箱、以种族为变量的主张以及促进描述性研究。我们认为,在定量研究中对这四个领域进行更深入的思考可以帮助研究人员做出定量分析所固有的艰难选择。
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来源期刊
Journal of Engineering Education
Journal of Engineering Education 工程技术-工程:综合
CiteScore
12.20
自引率
11.80%
发文量
47
审稿时长
>12 weeks
期刊介绍: The Journal of Engineering Education (JEE) serves to cultivate, disseminate, and archive scholarly research in engineering education.
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