Promoting a Diverse Computing Workforce: Using National Survey Data to Understand Persistence Across Undergraduate Student Groups

在计算机科学中，需要更多来自代表性不足群体的个人参与，这是有据可考的。这个项目利用了一个庞大的、多样化的数据集来更好地理解识别和自我效能的问题，这些问题有助于在计算机科学中代表性不足的群体中持续存在。该项目利用了一个现有的nsf资助的基础设施，该基础设施每年对参加各种计算项目的全国学生样本进行调查。具体来说，该项目利用了计算研究协会（CRA）的研究管道评估中心（CERP），该中心收集了来自各种机构类型和广泛人口群体的学生追求计算机职业轨迹的经历的大规模横断面调查数据。通过对来自不同学生群体和机构的大量广泛数据集的自我效能感和身份认同进行评估，可以更好地了解影响学生坚持学习的因素。这项被提议的研究对预测各种计算机学生群体的持久性很感兴趣。本研究的假设是：(1)自我效能感、职业价值观和社会认同威胁预测计算投入和坚持；(2)群体感知威胁的差异预测群体自我效能感的差异，进而预测群体投入和坚持的差异；(3)社会支持会减弱自我效能感和社会认同威胁对投入和预测的负面影响。在整个项目过程中，将进行两次调查，以评估所提出的学生坚持的理论模型。第一项调查将在全国范围内对计算机专业的本科生和研究生进行抽样调查，以衡量他们对计算机的投入程度和坚持的意愿，以及他们假设的预测因素。第二项调查将测量参与度和再次坚持的意图（即随着时间的变化），以及实际坚持。一系列的分析将检验理论化模型所涉及的每一个假设。结构方程建模将用于评估整体模型拟合和检查变量之间的关系。这项研究告知了最佳实践和新干预措施的发展，这些措施对全国范围内计算机科学中各种代表性不足的人群的保留产生了积极的影响。该项目将强大的理论背景和独特的社会科学视角与CERP提供的无与伦比的数据收集基础设施相结合。项目评估由咨询委员会在项目的所有阶段进行。要衡量的目标是所产生的数据的传播范围，以及使用这些数据的教育工作者和管理人员制定的干预措施的数量。与咨询委员会的持续联系可以从不同的学生群体中收集高质量的数据，并以一种对STEM教育感兴趣的普通受众可以访问和有用的方式传播结果。

The need for increased participation of individuals from underrepresented groups in computer science is well documented. This project makes use of a large, diverse data set to better understand the issues of identify and self-efficacy that contribute to persistence in underrepresented groups in computer science. The project capitalizes on an existing NSF-funded infrastructure that annually surveys a national sample of students enrolled in a diverse array of computing programs. Specifically, this project leverages the Computing Research Association's (CRA) Center for Evaluating the Research Pipeline (CERP), which collects large scale, cross sectional survey data concerning the experiences of students pursuing computing career tracks from a variety of institution types and from a wide array of demographic groups. By evaluating self-efficacy and identity across a large and broad data set from a diverse population of students and institutions, a much better picture of factors influencing student persistence is being generated.The proposed research is interested in predicting persistence among a variety of student groups in computing. The hypotheses that will guide this study are: (1) Self-efficacy, occupational values, and social identity threat predict engagement and persistence in computing, (2) Group differences in perceived threat will predict group differences in self-efficacy and, subsequently, group disparities in engagement and persistence, and (3) Social support will attenuate the negative effects of self-efficacy and social identity threat on engagement and prediction. Two surveys will be administered over the course of the project to assess the proposed theoretical model of student persistence. The first survey will be administered to a national sample of undergraduate and graduate computing students that will measure engagement and intentions to persist in computing and their hypothesized predictors. The second survey will measure engagement and intentions to persist again (i.e., changes over time), as well as actual persistence. A series of analyses will examine each of the hypotheses implicated by the theorized model. A structural equation modeling will be used to assess overall model fit and examine relations among variables.This research informs the development of best practices and new interventions that positively impact retention of a wide variety of underrepresented populations in computer science nationwide. This project combines a strong theoretical background and unique social science perspective with an unmatched data collection infrastructure provided by CERP. Project evaluation is conducted by an advisory board throughout all phases of the project. The objectives that will be measured are the scope of the dissemination of the data produced and the number of interventions developed by educators and administrators who use the data. Consistent contact with an advisory board results in the collection of high caliber data from a diverse population of students and the dissemination of results in a way that is a accessible and useful to a general audience with interest in STEM education.