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Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – Annenberg Institute for School Reform at Brown University, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Higher Education, Predictive Measurement, Models
Swail, Watson Scott; Fung-Angarita, Maly – Educational Policy Institute, 2018
The issue of student retention and graduation from postsecondary institutions has grown in stature over the past decade. While the last 40 years of federal and state policies have focused largely on access to college, there is now a very real interest in not only getting students into college but also helping them earn baccalaureate and other…
Descriptors: Data Collection, Postsecondary Education, College Students, School Holding Power
Hodara, Michelle; Xu, Di – American Educational Research Journal, 2016
Many community college students start college in developmental education and leave before enrolling in college-level coursework or making much progress toward a degree; thus, developmental education courses represent the primary education these students receive. Using student-unit record data from two large community college systems linked to wage…
Descriptors: Labor Market, Outcomes of Education, Evidence, Developmental Programs
Rutschow, Elizabeth Zachry; Richburg-Hayes, Lashawn; Brock, Thomas; Orr, Genevieve; Cerna, Oscar; Cullinan, Dan; Kerrigan, Monica Reid; Jenkins, Davis; Gooden, Susan; Martin, Kasey – MDRC, 2011
In 2004, Lumina Foundation for Education launched "Achieving the Dream: Community Colleges Count," a national initiative aimed at improving success among community college students, particularly low-income students and students of color. Now encompassing more than 130 institutions in 24 states and the District of Columbia, Achieving the…
Descriptors: Research Methodology, Program Descriptions, Student Characteristics, College Administration
Data Quality Campaign, 2010
Now that all 50 states and the District of Columbia are building statewide longitudinal data systems, the next step is to ensure that the information in these systems is used to improve student learning. The Data Quality Campaign (DQC) has identified 10 actions that states can take to ensure that the right data are available and accessible and…
Descriptors: Academic Achievement, Feedback (Response), High School Graduates, Graduation Rate
Kugle, Cherry; Smith, Nancy – Data Quality Campaign, 2006
The Data Quality Campaign is a national, collaborative effort to encourage and support state policymakers to improve the collection, availability and use of high-quality education data and to implement state longitudinal data systems to improve student achievement. The campaign aims to provide tools and resources that will assist state development…
Descriptors: Data Collection, Data Analysis, Longitudinal Studies, Academic Achievement