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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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Shi, Yang; Schmucker, Robin; Chi, Min; Barnes, Tiffany; Price, Thomas – International Educational Data Mining Society, 2023
Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…
Descriptors: Computer Science Education, Data Analysis, Programming, Coding
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
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Fouh, Eric; Farghally, Mohammed; Hamouda, Sally; Koh, Kyu Han; Shaffer, Clifford A. – International Educational Data Mining Society, 2016
We present an analysis of log data from a semester's use of the OpenDSA eTextbook system with the goal of determining the most difficult course topics in a data structures course. While experienced instructors can identify which topics students most struggle with, this often comes only after much time and effort, and does not provide real-time…
Descriptors: Item Response Theory, Data Analysis, Mathematics, Intelligent Tutoring Systems
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Huang, Francis L.; Cornell, Dewey G. – Journal of School Violence, 2012
School violence research is often concerned with infrequently occurring events such as counts of the number of bullying incidents or fights a student may experience. Analyzing count data using ordinary least squares regression may produce improbable predicted values, and as a result of regression assumption violations, result in higher Type I…
Descriptors: Violence, Bullying, Least Squares Statistics, Victims
Sonwalkar, Mukul Dinkar – ProQuest LLC, 2012
This dissertation addresses the use and modeling of spatio-temporal data for the purposes of providing applications for location based services. One of the major issues in dealing with spatio-temporal data for location based services is the availability and sparseness of such data. Other than the hardware costs associated with collecting movement…
Descriptors: Data Analysis, Geographic Location, Geographic Information Systems, Privacy
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Bicak, Ali; Liu, Michelle; Murphy, Diane – Information Systems Education Journal, 2015
The cybersecurity curriculum has grown dramatically over the past decade: once it was just a couple of courses in a computer science graduate program. Today cybersecurity is introduced at the high school level, incorporated into undergraduate computer science and information systems programs, and has resulted in a variety of cybersecurity-specific…
Descriptors: Information Security, Curriculum Design, Computer Science, Graduate Study
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Nagle, Katherine; Pratt-Williams, Jaunelle; Schmidt, Rebecca; Swantek, Cara; Lyulchenko, Marianna; McGhee, Raymond – Grantee Submission, 2016
This is the final external evaluation report prepared by SRI International for the Rural Math Excel Partnership (RMEP) project, an investing in innovation (i3) development project funded by the U.S. Department of Education. Operated by Virginia Advanced Study Strategies, Inc. (VASS), the RMEP project included six rural school districts (LEAs) in…
Descriptors: Rural Schools, Mathematics Education, Family Involvement, Mathematics Teachers
Rutherford, Jean – National Center for Educational Accountability, 2006
Governors and state and local education officials assumed that raising student achievement in the elementary and middle grades would solve the problems with high schools--but it hasn't. Why? Good information is the basis for successful improvement, and high school reform lacks accurate information about what students are to learn and about how…
Descriptors: High Schools, Educational Quality, School Effectiveness, Best Practices