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Ashley Haigler – ProQuest LLC, 2021
The results of an industry research survey showed, understanding Dissertation Research categories has not been the focused on many researchers and institutions. This research expands on machine learning methodologies using two similar datasets to answer these three questions: 1. Is there a way to track the trends of Pace University's Doctor of…
Descriptors: Artificial Intelligence, Content Analysis, Cluster Grouping, Classification
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Jabnoun, Naceur – Quality Assurance in Education: An International Perspective, 2015
Purpose: This paper aims to explore the influence of wealth, transparency and democracy on the number of universities per million people ranked among the top 300 and 500. The highly ranked universities in the world tend to be concentrated in a few countries. Design/Methodology/Approach: ANOVA was used to test the differences between the two groups…
Descriptors: Universities, Classification, Influences, Fiscal Capacity
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Soh, Kay Cheng – Higher Education Review, 2012
Three university ranking systems in vogue have been shown in the previous issue of "Higher Education Review" to be capable of modifications to make them more parsimonious by using only about half of the number of predictors currently in use. This makes some of the predictors "redundant" as they contributed little to the overall ranking. It is…
Descriptors: Higher Education, Predictor Variables, Profiles, Test Items
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Saenz, Victor B.; Hatch, Deryl; Bukoski, Beth E.; Kim, Suyun; Lee, Kye-hyoung; Valdez, Patrick – Community College Review, 2011
This study employs survey data from the Center for Community College Student Engagement to examine the similarities and differences that exist across student-level domains in terms of student engagement in community colleges. In total, the sample used in the analysis pools data from 663 community colleges and includes more than 320,000 students.…
Descriptors: Learner Engagement, Community Colleges, Classification, Multivariate Analysis
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Carpenter, Dick – Journal of School Choice, 2006
To date, few studies have quantitatively examined within-group differences among charter schools. This is largely due to the lack of a workable typology with which to describe and classify schools. This study fills that gap with a two dimensional typology constructed from a sample of 1182 charter schools in five states--Arizona, California,…
Descriptors: Charter Schools, Classification, Cluster Grouping, State Surveys
Rock, Donald A.; Evans, Franklin R. – 1971
Methodologies were proposed for combining background and aptitude and/or achievement information in an approach to the classification problem using the concept of under- and overachievement. The methodologies were applied to independent samples from four high school curricula. The results suggest that when past achievement and/or aptitudes were…
Descriptors: Academic Achievement, Aptitude Tests, Classification, Cluster Grouping