Exploration of Intersectionality and Computer Science Demographics: Understanding the Historical Context of Shifts in Participation
Exploration of Intersectionality and Computer Science Demographics: Understanding the Historical Context of Shifts in Participation
复制标题
交叉性和计算机科学人口统计的探索：理解参与转变的历史背景
DOI：
10.1145/3445985
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发表时间：
2021
影响因子：
2.4
通讯作者：
Ohland, Matthew
中科院分区：
文献类型：
--
作者：
Lunn, Stephanie;Zahedi, Leila;Ross, Monique;Ohland, Matthew
尽管计算机职业的预期增长率最高，但这些领域的毕业生仍然短缺。吸引足够多的学生来满足需求的困难，对于在计算机领域已经被低估的群体来说尤为明显，特别是那些自我认同为女性、黑人、西班牙裔/拉丁裔或美洲原住民的个人。以前的研究已经开始研究围绕参与和保留的问题，但需要更多的了解才能缩小差距，扩大参与。在这项研究中，我们从多机构调查工程纵向发展数据库中提供了定量证据，该数据库是一个纵向的、多机构的数据库，用于描述边缘群体参与计算机科学的趋势。使用描述性统计，我们展示了1987至2018年间那些位于种族/族裔和性别交叉点的学生的入学率和毕业率。在这项工作中，我们观察到黑人男性和女性，特别是白人女性的显著变化时期，以及西班牙裔/拉丁裔、美洲原住民和亚洲女性的参与率一直较低。为了提供明显的参与高峰和低谷的框架，我们应用历史背景分析来描述可能影响每个群体的政治、经济和社会因素和事件。这些结果让人们关注在统计工作中基本上被忽视的人群，并有可能让教育工作者、管理人员和研究人员了解计算机领域的入学率和毕业率是如何随着时间的推移而变化的。此外，它们还提供了对变化的潜在原因的洞察，以鼓励所有学生在前进中获得更平等的机会。
Although computing occupations have some of the greatest projected growth rates, there remains a deficit of graduates in these fields. The struggle to engage enough students to meet demands is particularly pronounced for groups already underrepresented in computing, specifically, individuals that self-identify as a woman, or as Black, Hispanic/Latinx, or Native American. Prior studies have begun to examine issues surrounding engagement and retention, but more understanding is needed to close the gap, and to broaden participation. In this research, we provide quantitative evidence from the Multiple-Institution Database for Investigating Engineering Longitudinal Development—a longitudinal, multi-institutional database to describe participation trends of marginalized groups in computer science. Using descriptive statistics, we present the enrollment and graduation rates for those situated at the intersection of race/ethnicity and gender between 1987 and 2018. In this work, we observed periods of significant flux for Black men and women, and White women in particular, and consistently low participation of Hispanic/Latinx and Native American men and women, and Asian women. To provide framing for the evident peaks and valleys in participation, we applied historical context analysis to describe the political, economic, and social factors and events that may have impacted each group. These results put a spotlight on populations largely overlooked in statistical work and have the potential to inform educators, administrators, and researchers about how enrollments and graduation rates have changed over time in computing fields. In addition, they offer insight into potential causes for the vicissitudes, to encourage more equal access for all students going forward.