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A Systematic Review Exploring the Differences in Reported Data for Pre-College Educational Activities for Computer Science, Engineering, and Other STEM Disciplines

机译:系统综述探讨了大学计算机科学,工程和其他词汇学科的大学教育活动数据的差异

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摘要

There has been considerable investment in pre-college educational interventions for all areas of STEM (including computer science). The goal of many of these initiatives is to engage and interest students early in their educational career. In this study, a systematic literature review was undertaken to determine the demographic and program data collected and reported for the field of computing education and for other STEM disciplines for activities that were not designed as part of the formal in-class curriculum (e.g., outreach activities). A comparison-contrast analysis of the resulting 342 articles found similarities and key differences in the reporting of this data as well as overarching characteristics of missing or incomplete reporting across disciplines. Authors from both fields reported equally well in the four categories studied: information about evaluation, participant gender, participant race and/or ethnicity, and activity demographics. However, the computing education articles were more likely to have clearly stated research questions and comparative analysis based on demographic characteristics. They were less likely to include the number of participants in the study, participant age/grade level, socioeconomic status, disability information, location of intervention, and instructor demographics. Through this analysis, it was determined that reporting can be improved across all disciplines to improve the quantity of data needed to replicate studies and to provide complete data sets that provide for the comparison of collected data.
机译:对大学前教育教育干预有相当大的投资(包括计算机科学)。许多这些举措的目标是在教育职业生涯早期吸引和兴趣。在这项研究中,进行了系统的文献综述,以确定收集的人口统计和计划数据,并报告了计算教育领域,并为其作为正式课程的一部分而非设计的活动(例如,OutReach)活动)。结果的342篇文章的比较 - 对比分析发现了该数据的报告中的相似之处和关键差异,以及跨学科的缺失或不完整的总体特征。来自两个领域的作者在研究的四个类别中同样良好地报告:有关评估,参与性别,参与者和/或种族的信息,以及活动人口统计学。然而,计算教育文章更有可能根据人口统计特征明确说明研究问题和比较分析。它们不太可能包括研究中的参与者人数,参与者年龄/年级,社会经济地位,残疾信息,干预位置和教练人口统计。通过上述分析,已确定报告可以在所有的学科加以改进,以提高需要重复研究的数据的数量,并提供完整的数据集提供了所收集的数据进行比较。

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