ECR Projects

Explore past and current fundamental STEM education research projects across the three research areas that NSF's EDU Core Research (ECR) program funds, as well as across ECR funding types. Other search filters draw from both NSF's data and the ECR Hub's hand coding of award abstracts.

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BIGDATA: EAGER: Using Big Data to Investigate Longitudinal Education Outcomes through Visual Analytics

Effective Years: 2015-2018

BIGDATA: Using Big Data to Investigate Longitudinal Education Outcomes through Visual Analytics

Data science techniques have revolutionized many academic fields and led to terrific gains in the commercial sector. They have to date been underutilized in solving critical problems in the US educational system, particularly in understanding Science, Technology, Engineering and Mathematics (STEM) learning and learning environments, broadening participation in STEM, and increasing retention for students traditionally underserved in STEM. The goals of the Directorate for Education and Human Resources (EHR), through the EHR Core Research program, for the Critical Techniques and Technologies for Advancing Foundations and Applications of Big Data Science & Engineering (BIGDATA) program are to advance fundamental research aimed at understanding and solving these critical problems, and to catalyze the use of data science in Education Research. This Early Concept Grant for Exploratory Research (EAGER) will employ data from national representative datasets including approximately 35,000 students to investigate course taking patterns in high school and how these relate to critical outcomes such as college attendance, high school and college success, and career choices. Few investigators have attempted to answer this question with this scale of data. Therefore, this proposal will contribute significantly to the field's understanding of factors that affect success in high school and college. Building on these new insights will enable the potential to create interventions at the high school and college level based on data about what works to improve graduation and workforce outcomes.

The Education Longitudinal Study of 2002-2012 (ELS:2002) and High School Longitudinal Study of 2009 (HSLS:2009) are representative samples of high school students who were tracked through college and into their early career. ELS has 15,000 students and HSLS has 21,000 students. For ELS, NCES surveyed students in 10th and 12th grade, then sophomore year of college, and then when they were approximately 26. NCES collected transcripts for high school and college, and high school and college achievement, attitudinal, participation and demographic variables. The Principal Investigator will first use visualizations to identify potential patterns of difference in outcomes and then use growth mixture modeling (GMM) and receiver operating characteristic analysis (ROC) to investigate the statistical significance of those patterns.

This award is supported by the EHR Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development