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Yiran Chen – Research in Higher Education, 2025
The "k"-means clustering method, while widely embraced in college student typology research, is often misunderstood and misapplied. Many researchers regard "k"-means as a near-universal solution for uncovering homogeneous student groups, believing its success hinges primarily on the selection of an appropriate "k."…
Descriptors: College Students, Classification, Educational Research, Research Methodology
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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Crisp, Gloria; Horn, Catherine L.; Kuczynski, Margaret; Zhou, Qiong; Cook, Elizabeth – Review of Higher Education, 2019
Study of four-year broad access institutions (BAIs) is important given their influence on postsecondary educational opportunities and the continued importance of the bachelor's degree in earnings premiums and critical social and civic outcomes. Descriptive results add to current understanding regarding heterogeneity of four-year BAIs by…
Descriptors: Inclusion, Classification, Institutional Characteristics, Admission Criteria
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Ravinder, Handanhal; Misra, Ram B. – American Journal of Business Education, 2014
ABC analysis is a well-established categorization technique based on the Pareto Principle for determining which items should get priority in the management of a company's inventory. In discussing this topic, today's operations management and supply chain textbooks focus on dollar volume as the sole criterion for performing the categorization. The…
Descriptors: Facility Inventory, Evaluation Methods, Classification, Administration
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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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Suranyi, Zsuzsanna; Hitchcock, David B.; Hittner, James B.; Vargha, Andras; Urban, Robert – International Journal of Behavioral Development, 2013
Previous research on sensation seeking (SS) was dominated by a variable-oriented approach indicating that SS level has a linear relation with a host of problem behaviors. Our aim was to provide a person-oriented methodology--a probabilistic clustering--that enables examination of both inter- and intra-individual differences in not only the level,…
Descriptors: Personality Traits, Behavior Problems, Conceptual Tempo, Individual Differences
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Rudner, Lawrence M.; Guo, Fanmin – Journal of Applied Testing Technology, 2011
This study investigates measurement decision theory (MDT) as an underlying model for computer adaptive testing when the goal is to classify examinees into one of a finite number of groups. The first analysis compares MDT with a popular item response theory model and finds little difference in terms of the percentage of correct classifications. The…
Descriptors: Adaptive Testing, Instructional Systems, Item Response Theory, Computer Assisted Testing
Gabe, Todd; Abel, Jaison R.; Ross, Adrienne; Stolarick, Kevin – Federal Reserve Bank of New York, 2010
This study identifies clusters of U.S. and Canadian metropolitan areas with similar knowledge traits. These groups--ranging from Making Regions, characterized by knowledge about manufacturing, to Thinking Regions, noted for knowledge about the arts, humanities, information technology, and commerce--can be used by analysts and policymakers for the…
Descriptors: Foreign Countries, Identification, Metropolitan Areas, Human Capital
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Bahr, Peter Riley – Research in Higher Education, 2010
The development of a typology of community college students is a topic of long-standing and growing interest among educational researchers, policy-makers, administrators, and other stakeholders, but prior work on this topic has been limited in a number of important ways. In this paper, I develop a behavioral typology based on students'…
Descriptors: Community Colleges, Educational Research, Enrollment Trends, Classification
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Amershi, Saleema; Conati, Cristina – Journal of Educational Data Mining, 2009
In this paper, we present a data-based user modeling framework that uses both unsupervised and supervised classification to build student models for exploratory learning environments. We apply the framework to build student models for two different learning environments and using two different data sources (logged interface and eye-tracking data).…
Descriptors: Supervision, Classification, Models, Educational Environment