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Yi Wang; E. Michael Bohlig; Sandra L. Dika – New Directions for Community Colleges, 2025
Using data from the 2019 Community College Survey of Student Engagement (CCSSE) 3-year cohort, this article presents a validation study of the 2017 version of CCSSE. Exploratory and confirmatory factor analyses were implemented to investigate the psychometric properties and construct validity with strategies to address missing data. Eight…
Descriptors: Learner Engagement, Community Colleges, Community College Students, Construct Validity
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Karma El Hassan – Quality Assurance in Education: An International Perspective, 2013
Purpose: The American University of Beruit has generated a model for student success that builds on Kuh's five benchmarks of academic practice. The purpose of this study is to investigate the psychometric properties of the measures used to assess effectiveness of the benchmarks. Design/methodology/approach: Using a database of student responses to…
Descriptors: Construct Validity, Benchmarking, Correlation, Factor Analysis
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Sharma, Vandna – International Journal of Educational Management, 2012
Purpose: The environmental challenges of digitalization, globalization, and industrialization, which are growing at a fast pace, require serious attention. As a result, the old structures of the education system established in pre-independent India and in place during most of the twentieth century are now required to undergo drastic changes. The…
Descriptors: Knowledge Management, Management Systems, Global Approach, Factor Analysis
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LaNasa, Steven M.; Cabrera, Alberto F.; Trangsrud, Heather – Research in Higher Education, 2009
As institutions seek to promote student engagement on campus, the National Survey of Student Engagement (NSSE) is increasingly being used to chart progress and compare results using the Five Benchmark Scores. While recent research has begun to decompose the five benchmarks in a variety of ways; few research studies have sought to explore the…
Descriptors: College Students, Construct Validity, Factor Analysis, Learner Engagement