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Showing 1 to 15 of 21 results Save | Export
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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Papay, Clare; Grigal, Meg; Hart, Debra; Kwan, Ngai; Smith, Frank A. – Intellectual and Developmental Disabilities, 2018
Higher education programs for students with intellectual and developmental disabilities (IDD) offer opportunities to engage in college experiences including access to typical college courses. The purpose of the present study was to examine data from federally funded programs in order to describe and identify predictors of inclusive course…
Descriptors: Enrollment, College Freshmen, Intellectual Disability, Inclusion
Marini, Jessica; Shaw, Emily; Young, Linda; Ewing, Maureen – College Board, 2018
This study investigated differences in college grading practices (first-year grade point average and course grades) by student and institutional characteristics and by academic discipline to inform and improve our understanding and use as among the most commonly employed criteria in validity and college readiness research. In addition, trends in…
Descriptors: Higher Education, Grading, College Students, Student Characteristics
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Barra, Cristian; Zotti, Roberto – Tertiary Education and Management, 2017
The main purpose of the paper is to estimate the efficiency of a big public university in Italy using individual student-level data, modeling exogenous variables in human capital formation through a heteroscedastic stochastic frontier approach. Specifically, a production function for tertiary education has been estimated with emphasis on…
Descriptors: Efficiency, School Statistics, Student Records, Information Utilization
Lee, Katelyn; Therriault, Susan – College and Career Readiness and Success Center, 2016
This brief examines strategies for leveraging State longitudinal data systems (SLDS) to promote college and career readiness (CCR) goals. The examples provided are based on current state efforts to use their state longitudinal data systems to achieve their CCR vision and goals. The following information outlines the basic purpose and elements of…
Descriptors: Longitudinal Studies, Career Readiness, College Readiness, Elementary Secondary Education
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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
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Khan, R. Nazim – International Journal of Mathematical Education in Science and Technology, 2015
Open book assessment is not a new idea, but it does not seem to have gained ground in higher education. In particular, not much literature is available on open book examinations in mathematics and statistics in higher education. The objective of this paper is to investigate the appropriateness of open book assessments in a first-year business…
Descriptors: Evaluation Methods, Higher Education, Mathematics Tests, Statistics
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Christian, David; Lawrence, Amy; Dampman, Nicole – Journal of College Access, 2017
High school counselors play a key role in increasing students' access to college. With increasing student-to-counselor ratios as well as demands on their time, school counselors often lack the ability to provide adequate college counseling. In this article, we explored how school counselors can use educational technology, specifically the online…
Descriptors: Access to Education, Higher Education, Postsecondary Education, High Schools
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Mah, Dana-Kristin – Technology, Knowledge and Learning, 2016
Learning analytics and digital badges are emerging research fields in educational science. They both show promise for enhancing student retention in higher education, where withdrawals prior to degree completion remain at about 30% in Organisation for Economic Cooperation and Development member countries. This integrative review provides an…
Descriptors: Educational Research, Data Collection, Data Analysis, Recognition (Achievement)
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Crawford, Ian; Wang, Zhiqi – Teaching in Higher Education, 2015
The main controversy as a result of the commercialisation of international education markets is that international students especially those from China are unable to perform as well as UK students in UK universities. So far, research has yet to identify the influence of placements on the academic performance of Chinese students from entry to…
Descriptors: Foreign Countries, Higher Education, Academic Achievement, Job Placement
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Schofield, Cathy; Dismore, Harriet – Journal of Further and Higher Education, 2010
Following recent developments within higher education where provision of foundation degree courses at further education colleges has been extended, it seemed appropriate to investigate the extent to which the system is working. This should not necessarily be measured by the number of students enrolling, but rather by how many are achieving their…
Descriptors: Higher Education, Grade Point Average, Academic Achievement, Adult Education
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Olani, Aboma – Electronic Journal of Research in Educational Psychology, 2009
Introduction: Premature withdrawal from university due to academic failure can present problems for students, families and educators. In an effort to widen the understanding regarding factors predicting academic success in higher institutions, prior academic achievement measures (preparatory school grade average point (GPA), aptitude test scores,…
Descriptors: Foreign Countries, Higher Education, Withdrawal (Education), Grade Point Average
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Jackson, Evelyn W.; Dawson-Saunders, Beth – Journal of Medical Education, 1987
A study found that variables significant in predicting minority students with academic difficulty include science grade-point average, Medical College Admission Test (MCAT) reading subtest score, and number of course withdrawals. For majority students, they include MCAT biology subtest score and number of incompletes taken in courses. (MSE)
Descriptors: Academic Persistence, Educational Background, Higher Education, Medical Education
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Fadem, Barbara H.; And Others – Journal of Medical Education, 1984
A discriminant analysis of objective and subjective measures from the records of students who graduated from the University of Medicine and Dentistry of New Jersey-New Jersey Medical School over a six-year period was used to generate a model for the prediction of medical specialty choice. (Author/MLW)
Descriptors: Career Choice, Discriminant Analysis, Graduates, Higher Education
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Handelman, Stanley; And Others – Journal of Dental Education, 1983
The relative value of academic standing, letters of recommendation, and personal interview impressions as predictors of performance during general dentistry training programs was assessed. Academic standing was the best predictor, with personal interview and recommendation letters next. (MSE)
Descriptors: Academic Achievement, Admission Criteria, Dental Students, Graduate Medical Education
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