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

有充分的文件证明，需要增加来自代表性不足群体的个人参与计算机科学。 这个项目利用了一个大型的，多样化的数据集，以更好地了解身份和自我效能的问题，有助于在计算机科学中的代表性不足的群体的持久性。 该项目利用了现有的NSF资助的基础设施，每年调查一个全国性的样本，学生参加了各种各样的计算程序。具体来说，该项目利用计算研究协会（CRA）的中心评估研究管道（CERP），收集大规模的，横截面的调查数据，有关学生的经验，追求计算职业轨道从各种机构类型和广泛的人口群体。 通过评估自我效能和身份在一个大的和广泛的数据集，从不同的人口的学生和机构，一个更好的图片影响学生的持久性的因素正在生成。拟议的研究是有兴趣在预测持久性之间的各种学生群体在计算。指导本研究的假设是：（1）自我效能、职业价值观和社会认同威胁预测了参与和持久性，（2）感知威胁的群体差异将预测自我效能的群体差异，随后预测参与和持久性的群体差异，（3）社会支持会减弱自我效能和社会认同威胁对投入和预测的负向影响。 在项目实施过程中将进行两次调查，以评估拟议的学生坚持学习的理论模式。 第一项调查将对全国范围内的本科生和研究生计算机专业的学生进行抽样调查，以衡量他们在计算机领域的参与度和坚持意愿以及他们假设的预测因素。 第二项调查将衡量参与度和再次坚持的意图（即，随着时间的推移而变化），以及实际的持久性。 一系列的分析将检查理论模型所涉及的每一个假设。 一个结构方程模型将被用来评估整体模型拟合和检查变量之间的关系。这项研究通知的最佳实践和新的干预措施，积极影响保留各种各样的代表性不足的人口在全国范围内的计算机科学发展。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。 项目评价由一个咨询委员会在项目的所有阶段进行。 将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行政人员制定的干预措施的数量。 与咨询委员会的持续联系导致从不同的学生群体中收集高质量的数据，并以一种对STEM教育感兴趣的普通观众可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.