A Decade of Demographics in Computing Education Research: A Critical Review of Trends in Collection, Reporting, and Use
A Decade of Demographics in Computing Education Research: A Critical Review of Trends in Collection, Reporting, and Use
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DOI：
10.1145/3501385.3543967
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发表时间：
2022-08
期刊：
影响因子：
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通讯作者：
A. Oleson;Benjamin Xie;Jean Salac;Jayne Everson;F. M. Kivuva;Amy J. Ko
中科院分区：
文献类型：
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作者：
A. Oleson;Benjamin Xie;Jean Salac;Jayne Everson;F. M. Kivuva;Amy J. Ko
计算教育研究（CER）使用人口统计数据来了解学习者的身份，背景和环境，例如文化响应的计算从非主导群体中进一步边缘化的人的结构。 . We conducted a content analysis of 510 peer-reviewed papers published in 12 CER venues from 2012 to 2021. We found that (1) 60% of papers studioded older learners in formal contexts (i.e. post-secondary education); (2) 68论文的百分比尚不清楚研究人员如何收集人口统计学数据，而94％的论文是单一站点的研究，只有14％的人解决了其上下文的局限性。潜水员）在23％的论文中，通过不完整的人口统计报告（即，在其样本中遗漏了某些参与者的人口统计学），我们在35％的论文中讨论了这些发现对CER领域的含义，这提出了CER研究人员的考虑。在收集，报告和使用人口统计数据时请记住。
Computing education research (CER) has used demographic data to understand learners’ identities, backgrounds, and contexts for efforts such as culturally-responsive computing. Prior work indicates that failing to elucidate and critically engage with the implicit assumptions of a field can unintentionally reinforce power structures that further marginalize people from non-dominant groups. The goal of this paper is two-fold: to understand what populations CER researchers have studied, and to surface implicit assumptions about how researchers have collected, reported, and used demographic data on these populations. We conducted a content analysis of 510 peer-reviewed papers published in 12 CER venues from 2012 to 2021. We found that (1) 60% of papers studied older learners in formal contexts (i.e. post-secondary education); (2) 68% of papers left unclear how researchers collected demographic data; and (3) while 94% of papers were single-site studies, only 14% addressed the limitations of their contexts. We also identified hegemonic norms through ambiguous aggregate term usage (e.g. underrepresented, diverse) in 23% of papers, and through incomplete reporting of demographics (i.e. leaving out demographics for some participants in their sample) in 35% of papers. We discuss the implications of these findings for the CER field, raising considerations for CER researchers to keep in mind when collecting, reporting, and using demographic data.