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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
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
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
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
Glazer, Randy – ProQuest LLC, 2019
Employee turnover continues to be discussed as an outcome in Human Resources (HR), but comparatively few studies have examined the relationship between turnover as the independent variable and institutional outcomes. Although the call to HR practitioners has often been made over the past 20 years regarding the importance of tying HR programs and…
Descriptors: Labor Turnover, Employees, Correlation, Human Resources
Raju, Dheeraj; Schumacker, Randall – Journal of College Student Retention: Research, Theory & Practice, 2015
The study used earliest available student data from a flagship university in the southeast United States to build data mining models like logistic regression with different variable selection methods, decision trees, and neural networks to explore important student characteristics associated with retention leading to graduation. The decision tree…
Descriptors: Student Characteristics, Higher Education, Graduation Rate, Academic Persistence
Miller, Nathan Brad; Bell, Bryan – Journal of Continuing Higher Education, 2016
Increased federal attention to student completion metrics and uncertain financial forecasts have heightened the tenor of student retention conversations. Improved institutional retention rates will lead to higher completion rates and relieve some funding concerns. To accomplish these improvements, institutions have invested in analytics to better…
Descriptors: Academic Persistence, School Holding Power, Acceleration (Education), Communication Strategies
Phillips, Brad C.; Horowitz, Jordan E. – New Directions for Community Colleges, 2013
The completion agenda is in full force at the nation's community colleges. To maximize the impact colleges can have on improving completion, colleges must organize around using student progress and outcome data to monitor and track their efforts. Unfortunately, colleges are struggling to identify relevant data and to mobilize staff to review…
Descriptors: Community Colleges, Academic Persistence, College Role, Data Collection
Gross, Jacob P. K.; Zerquera, Desiree; Inge, Brittany; Berry, Matthew – Journal of Hispanic Higher Education, 2014
Lack of financial resources to pay for postsecondary education--perceived and actual--has been cited as a barrier to student access and persistence, particularly for Latino students. This study investigates the following question: "To what extent does financial aid affect the educational attainment of Latinos enrolled in Associate's degree…
Descriptors: Associate Degrees, Hispanic American Students, Graduation Rate, Student Financial Aid
Ragland, Sheri E. – ProQuest LLC, 2016
In 2008, state legislatures provided $6 billion in financial aid to 2 million low-income young adults. When low-income young adults receive state financial aid and do not complete college, states lose their investment because fewer people with degrees will contribute to the state's economy. Declining states' budgets have led to (a) the rising cost…
Descriptors: Student Financial Aid, State Policy, Graduation Rate, Correlation
Education Trust, 2016
All across the country, leaders in colleges and universities are asking the same question: What can we do to improve student success, especially for the low-income students and students of color whose graduation rates often lag behind? This second practice guide: "Using Data to Improve Student Outcomes: Learning from Leading Colleges"…
Descriptors: Data Analysis, Information Utilization, Student Improvement, Outcomes of Education
Bogetoft, Peter; Wittrup, Jesper – School Effectiveness and School Improvement, 2017
This paper discusses methods for benchmarking vocational education and training colleges and presents results from a number of models. It is conceptually difficult to benchmark vocational colleges. The colleges typically offer a wide range of course programmes, and the students come from different socioeconomic backgrounds. We solve the…
Descriptors: Benchmarking, Vocational Education, Models, Postsecondary Education
Knowles, Jared E. – Journal of Educational Data Mining, 2015
The state of Wisconsin has one of the highest four year graduation rates in the nation, but deep disparities among student subgroups remain. To address this the state has created the Wisconsin Dropout Early Warning System (DEWS), a predictive model of student dropout risk for students in grades six through nine. The Wisconsin DEWS is in use…
Descriptors: Dropouts, Models, Prediction, Risk
Douglas, Daniel; Attewell, Paul – American Journal of Education, 2014
College graduation rates in the United States are low in both real and relative terms. This has left all stakeholders looking for novel solutions while perhaps ignoring extant but underused programs. This article examines the effect of "summer bridge" programs, which have students enroll in coursework prior to beginning their first full…
Descriptors: Summer Programs, Academic Achievement, Program Effectiveness, College Preparation
Nandeshwar, Ashutosh R. – ProQuest LLC, 2010
In the modern world, higher education is transitioning from enrollment mode to recruitment mode. This shift paved the way for institutional research and policy making from historical data perspective. More and more universities in the U.S. are implementing and using enterprise resource planning (ERP) systems, which collect vast amounts of data.…
Descriptors: Higher Education, Institutional Research, Graduation Rate, Program Effectiveness

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