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Lee, Chansoon – Educational Measurement: Issues and Practice, 2022
Appropriate placement into courses at postsecondary institutions is critical for the success of students in terms of retention and graduation rates. To reduce the number of students who are misplaced, using multiple measures in placing students is encouraged. However, in practice most postsecondary schools utilize only a few measures to determine…
Descriptors: Classification, Models, Student Placement, College Students
Cem Recai Çirak; Hakan Akilli; Yeliz Ekinci – Higher Education Quarterly, 2024
In this study, an early warning system predicting first-year undergraduate student academic performance is developed for higher education institutions. The significant factors that affect first-year student success are derived and discussed such that they can be used for policy developments by related bodies. The dataset used in experimental…
Descriptors: Program Development, At Risk Students, Identification, College Freshmen
Hughes, John; Petscher, Yaacov – Regional Educational Laboratory Southeast, 2016
The high rate of students taking developmental education courses suggests that many students graduate from high school unready to meet college expectations. A college readiness screener can help colleges and school districts better identify students who are not ready for college credit courses. The primary audience for this guide is leaders and…
Descriptors: College Readiness, Screening Tests, Test Construction, Predictor Variables
Schloss, Patrick J. – Diagnostique, 1985
An alternative approach to the traditional diagnostic-prescrptive or medical model for classifying behavior disorders is proposed which considers topography of deviant behaviors, degree of exceptionality, nature of deviance, and events influencing the deviancy in the context of developing and monitoring education/treatment programs. (Author/CB)
Descriptors: Behavior Disorders, Classification, Disability Identification, Educational Diagnosis
Peer reviewedJones, Thomas W. – Volta Review, 1984
Approaches to identifying, classifying, and placing multiply handicapped hearing impaired students are reviewed, and a model is described in which five factors differentiate among students: instructional objectives, environment, rate, methodology, and staffing. (CL)
Descriptors: Classification, Disability Identification, Hearing Impairments, Models
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
Peer reviewedPatton, James M. – Journal of Special Education, 1998
Reviews the continuing overrepresentation of African-American children and youth in special education programs for students with learning disabilities, severe emotional or behavioral disabilities, and mental disabilities. Uses a critical-theory model to examine how basic assumptions, world views, beliefs, and epistemologies serve to perpetuate…
Descriptors: Attitudes, Behavior Disorders, Black Students, Classification

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