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Matthew J. Capaldi – Journal of College Student Retention: Research, Theory & Practice, 2025
This study explores the association between having a transit stop within walking distance of campus and Pell Grant recipient completion rates at US commuter institutions, using a novel dataset on transit stop locations and institutional level data. The findings indicate that there is a positive association between transit access and Pell…
Descriptors: Federal Aid, Grants, Proximity, Commuter Colleges
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Achmad Bisri; Supardi; Yayu Heryatun; Hunainah; Annisa Navira – Journal of Education and Learning (EduLearn), 2025
In the educational landscape, educational data mining has emerged as an indispensable tool for institutions seeking to deliver exceptional and high-quality education. However, education data revealed suboptimal academic performance among a significant portion of the student population, which consequently resulted in delayed graduation. This…
Descriptors: Data Analysis, Models, Academic Achievement, Evaluation Methods
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Juan Pablo Salazar-Fernandez; Jorge Munoz-Gama; Marcos Sepúlveda – Higher Education: The International Journal of Higher Education Research, 2025
Understanding how students with low socioeconomic status finance their tuition over time can help us comprehend the impact of students' decisions on their subsequent curricular progress, graduation, or dropout. This work presents a curricular analytics approach using process mining techniques to study educational funding trajectories as processes.…
Descriptors: Scholarships, Merit Scholarships, Student Needs, Learning Trajectories
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Comunale, Christie L.; Sexton, Thomas R.; Higuera, Michael Shane; Stickle, Kelly – Educational Research Quarterly, 2021
State education departments find themselves pressured to reduce costs while improving student performance. To do so, state education departments must measure the performance of each school district in an objective, data-informed manner. We present a benchmarking methodology and illustrate its application in New York State school districts. We…
Descriptors: School Districts, Academic Achievement, Standardized Tests, Graduation Rate
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Bird, Kelli A.; Castleman, Benjamin L.; Song, Yifeng; Mabel, Zachary – Education Next, 2021
An estimated 1,400 colleges and universities nationwide have invested in predictive analytics technology to identify which students are at risk of failing courses or dropping out, with spending estimated in the hundreds of millions of dollars. How accurate and stable are those predictions? The authors put six predictive models to the test to gain…
Descriptors: Prediction, Models, Data Analysis, Community Colleges
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Robert Todd Hicks; John R. Slate; Janene W. Hemmen – Education Leadership Review, 2024
In this article, industry-based certification attainment rates were compared by student ethnicity/race as reported by the Texas Education Agency for the 2019-2020, 2020-2021, and 2021-2022 school years. Through analyses of Texas statewide data, statistically significant differences were revealed in industry-based certification attainment rates…
Descriptors: High School Graduates, Ethnicity, Race, Educational Attainment
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Li Feng; Eleanor W. Close; Cynthia J. Luxford; Jiwoo An Pierson; Alice Olmstead; Jieon Shim; Venkata Sowjanya Koka; Heather C. Galloway – Research in Higher Education, 2025
Evidence-based and student-centered instructional methods hold the promise of transforming undergraduate STEM education and simultaneously solving the dual challenge of STEM workforce needs and inequities within STEM. The Learning Assistant (LA) Model was created to reform curriculum, recruit teachers, and inform discipline-based education…
Descriptors: STEM Education, School Holding Power, Graduation Rate, Data Analysis
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Wang, Rong; Orr, James E., Jr. – Journal of College Student Retention: Research, Theory & Practice, 2022
Higher education institutions have prioritized supporting undecided students with their major and career decisions for decades. This study used a U.S. public research-focused university's large-scale institutional data set and undecided student's retention and graduation rate predictors to demonstrate how to couple student and institutional data…
Descriptors: Data Use, Decision Making, Predictor Variables, Academic Advising
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Cardona, Tatiana; Cudney, Elizabeth A.; Hoerl, Roger; Snyder, Jennifer – Journal of College Student Retention: Research, Theory & Practice, 2023
This study presents a systematic review of the literature on the predicting student retention in higher education through machine learning algorithms based on measures such as dropout risk, attrition risk, and completion risk. A systematic review methodology was employed comprised of review protocol, requirements for study selection, and analysis…
Descriptors: Learning Analytics, Data Analysis, Prediction, Higher Education
Christina Ciocca Eller – Annenberg Institute for School Reform at Brown University, 2019
The rise of accountability standards has pressed higher education organizations to oversee the production and publication of data on student outcomes more closely than in the past. However, the most common measure of student outcomes, average bachelor's degree completion rates, potentially provides little information about the direct impacts of…
Descriptors: Higher Education, Accountability, Graduation Rate, Bachelors Degrees
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Schuck, Amie M. – Research in Higher Education, 2017
The goal of this study is to evaluate the effect of crime and discipline on graduation rates in higher education. Using national data on more than 1250 public and private non-profit institutions that were drawn from the Integrated Postsecondary Education Data System, the results reveal that more violence on and around campus is associated with…
Descriptors: Crime, Discipline, Academic Achievement, Graduation Rate
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Shea, Peter; Bidjerano, Temi – International Review of Research in Open and Distributed Learning, 2018
Recent research indicates that certain students are at risk of lower levels of academic performance in online settings when compared to peers who study only in the classroom. Community college students have been a population of particular concern. In this paper, we hypothesize that online course load and institutional quality may impact outcomes…
Descriptors: Online Courses, Enrollment, Community Colleges, Graduation
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Coleman, Chad; Baker, Ryan S.; Stephenson, Shonte – International Educational Data Mining Society, 2019
Determining which students are at risk of poorer outcomes -- such as dropping out, failing classes, or decreasing standardized examination scores -- has become an important area of research and practice in both K-12 and higher education. The detectors produced from this type of predictive modeling research are increasingly used in early warning…
Descriptors: Prediction, At Risk Students, Predictor Variables, Elementary Secondary Education
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Bingham, Melissa A.; Solverson, Natalie Walleser – Journal of Student Affairs Research and Practice, 2016
First- to second-year retention rates are one metric reported by colleges and universities to convey institutional success to a variety of external constituents. But how much of a retention rate is institutional inputs, and how much can be understood by examining student inputs? The authors utilize multi-year, multi-institutional data to examine…
Descriptors: Public Colleges, Universities, College Students, School Holding Power
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Wainerman, Catalina; Matovich, Iván – Education Policy Analysis Archives, 2016
Since the mid-1990s, there has been an abrupt growth of doctoral enrollments and doctoral programs in Argentina and Latin America. However, completion rates at this education level are far from satisfying. Attrition rates in Social Sciences doctoral programs "are known" to be high, and higher in Social Sciences and Humanities (which will…
Descriptors: Doctoral Programs, Time to Degree, STEM Education, Foreign Countries
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