Collaborative Proposal: A Data-Intensive Exploration of the Links Between SES and STEM Learning Outcomes

家庭社会经济地位与学生在STEM和其他学科的学习之间的联系，在文献中得到了很好的说明。然而，用于这些研究的数据的性质相当粗略，越来越难以获得，因为学校不再需要决定谁有资格享受免费和降价午餐。该项目的研究人员将使用补充营养援助计划(SNAP)或食品券数据利用数据作为社会经济地位(SES)的替代指标，以确定此类数据的效用。此外，越来越多的教育工作者被鼓励使用数据来为决策提供信息，尽管可用的数据和数据表示并不总是足以供教育工作者使用。收集和组织数据的研究人员和利益相关者之间的协作互动为更好地解释数据提供了强有力的支持。这项探索性研究是IDEA数据密集型研究实验室的一部分，研究人员将研究使用SNAP数据通过日常交易数据测量的学生SES模式波动与多个STEM成绩、行为推荐和出勤结果之间的关系。研究人员还将审查所确定的关系可以在多大程度上以对包括学校工作人员和在青年服务组织工作的人在内的各种利益攸关方有用的方式进行可视化。三个研究问题将构成本研究的结构如下：1)。如何使用SNAP交易数据和学生成绩数据来探索SES的时间变化与STEM学习结果之间的关系？利益相关者如何基于数据密集的分析和学生时变的SES的可视化来理解和构建行动的含义？利益相关者需要什么支持才能构建行动含义并参与协作数据分析？北卡罗来纳州卫生与公众服务部提供的食品券数据将与从杜克大学北卡罗来纳州教育研究数据中心获得的学生数据相结合。这些数据将使用纵向数据分析模型、可视化数据分析和多层次建模技术进行分析。来自北卡罗来纳州达勒姆学区的利益相关者将包括来自学区K-12学校和青年服务组织的教师、管理人员和辅导员。这项研究与实践者的合作将确定关于学生的新数据和新的数据可视化如何支持解释，从而增强利益相关者与学生在STEM中的成功相关的决策。

The links between family SES and students' learning, in STEM and other disciplines, is well noted in the literature. However, the nature of the data that has been used for these studies is quite coarse grained and is increasingly hard to get as schools are no longer required to determine who is eligible for free and reduced-price lunch. The researchers in this project will use Supplemental Nutrition Assistance Program (SNAP) or food stamps data utilization data as a proxy for socioeconomic status (SES) to determine the utility of such data. In addition, educators are increasingly exhorted to use data to inform decision-making, though the data available and the data representations are not always sufficient for educator use. The collaborative interaction between researchers collecting and organizing data and stakeholders who are brought together to make sense of the data provides the strong context in which better interpretations of data are supported.The researchers in this exploratory study funded as part of the Ideas Lab for Data Intensive Research will examine the relationships among fluctuations in patterns of students' SES measured by daily transaction data using SNAP data and multiple STEM achievement, behavioral referral, and attendance outcomes. The researchers will also examine the extent to which the relationships identified can be visualized in ways that have utility to various stakeholders including school staff and those who work in youth-serving organizations. Three research questions will structure this research as follows: 1). In what ways can SNAP transaction data and student achievement data be used to explore the relationships between temporal variation in SES and STEM learning outcomes?; 2). How do stakeholders make sense of and how do they construct implications for action based on data intensive analyses and visualizations of students' time-varying SES?; and, 3). What supports do stakeholders need in order to construct implications for action and engage in collaborative data analyses? Food stamp data provided from North Carolina's Department of Health and Human Services will be integrated with data on students' data obtained from the North Carolina Education Research Data Center at Duke University. These data will be analyzed with longitudinal data analysis models, visual data analytics, and multi-level modeling techniques. Stakeholders from the Durham, North Carolina school district will include teachers, administrators and counselors from the districts' K-12 schools and youth-serving organizations. This research-practitioner collaboration will identify ways in which new data about students and new data visualizations support interpretations that enhance stakeholder's decision-making related to students' success in STEM.