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Kidzinsk, Lukasz; Sharma, Kshitij; Boroujeni, Mina Shirvani; Dillenbourg, Pierre – International Educational Data Mining Society, 2016
The big data imposes the key problem of generalizability of the results. In the present contribution, we discuss statistical tools which can help to select variables adequate for target level of abstraction. We show that a model considered as over-fitted in one context can be accurate in another. We illustrate this notion with an example analysis…
Descriptors: Generalizability Theory, Online Courses, Large Group Instruction, Models
Kong, Jadie; Powers, Sonya; Starr, Laura; Williams, Natasha – Pearson, 2012
The purpose of this study was to investigate the use of English language proficiency and academic reading assessment scores to predict the future academic success of English learner (EL) students. Data from two cohorts of middle-school ELs were used to evaluate three prediction models. One cohort of students was used to develop the prediction…
Descriptors: English Language Learners, Academic Achievement, Language Proficiency, Reading Tests
Womack, Sid T.; Hanna, Shellie L.; Callaway, Rebecca; Woodall, Peggy – Online Submission, 2011
Differences in intern performance, as measured by a Praxis III-similar instrument were found between interns supervised in three supervisory models: Traditional triad model, cohort model, and distance supervision. Candidates in this study's particular form of distance supervision were not as effective as teachers as candidates in traditional-triad…
Descriptors: Supervisory Methods, Models, Performance Based Assessment, Internship Programs
Hauser, Carl – 2003
This study was undertaken to evaluate models that could be used to set single-year individual student academic growth targets. Multiple terms of individual student reading and mathematics test results were analyzed to predict each student's final status score in each subject. Test records from more than 5,300 students in 3 cohorts were used; 2…
Descriptors: Accountability, Cohort Analysis, Elementary Secondary Education, Individual Differences
Gonzalez, Julie M. Byers; DesJardins, Stephen L. – 2001
This paper examines how predictive modeling can be used to study application behavior. A relatively new technique, artificial neural networks (ANNs), was applied to help predict which students were likely to get into a large Research I university. Data were obtained from a university in Iowa. Two cohorts were used, each containing approximately…
Descriptors: Cohort Analysis, College Applicants, Comparative Analysis, Higher Education
Tatham, Elaine L. – 1977
The author describes her career development from mathematics instructor to director of institutional research at a large community college. She discusses the impact of mathematics on her career, illustrates her present job by describing three recently completed research projects, and strongly recommends that mathematics instructors encourage some…
Descriptors: Cohort Analysis, Community Colleges, Demography, Enrollment Projections
Brazziel, William F. – 1988
This paper examines the changing demographics of American society and the impact of these changes on higher education. Discussions include a historical background of early American demography, the building and expansion of the population base, and census changes through various generations of the baby boom years and beyond. Next, the report…
Descriptors: Adult Education, Baby Boomers, Birth Rate, Census Figures
Neblock, Carl S. – 1996
The use of the cohort-survival method for projecting student enrollments is widely known in educational finance literature; however, the limited information provided by the model impedes planners in making future operational decisions. The cohort-survival method employs historical rates of usage to predict future patterns of usage and produces a…
Descriptors: Algorithms, Bilingual Education, Cohort Analysis, Compensatory Education