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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
41

Predictors of Educational Outcomes among Undergraduate Students with Disabilities

Ruderman, Danielle Eve 05 July 2013 (has links)
No description available.
42

Relationships Between Institutional Characteristics and Student Retention and Graduation Rates at SACSCOC Level III Institutions

Perkins-Holtsclaw, Kala 01 May 2018 (has links) (PDF)
As the United States struggles to be globally competitive with the number of students completing a college degree higher education leaders continue seeking answers to improving student retention and graduation rates. Decades of research has been conducted on investigating factors that impact student retention and graduation with the majority of that research being centered on student attributes and students’ precollege characteristics. Research has been limited on institutional characteristics and their associations with student retention and graduation rates. Therefore the purpose of this study was to examine the extent that specific institutional characteristics predict first-year, full-time, fall-to-fall retention rates and 6-year graduation rates. The sample for this study consisted of 4-year institutions in the Southern Association of Colleges and Schools Commission on Colleges (SACSCOC) region that have been granted Level III accreditation status and also report data annually to the Integrated Postsecondary Data System (IPEDS). All data used for this research were publicly available archival data available from IPEDS. Sixteen research questions were investigated about institutional student variables, environment variables, resource variables, financial variables, and interaction variables. Multiple linear regressions were conducted for all research questions, representing the statistical method of analysis. The findings showed that the most useful predictors for retention rates were students scoring at or above the 75th percentile ACT scores, physical library collections, expenditures for academic support, and tuition and required fees. When investigating to what extent institutional characteristics predict 6-year graduation rates the findings showed that 75th percentile ACT scores, physical library collections, expenditures for instruction, the percentage of full-time faculty, and cost were the most useful predictors. Findings also showed that student-faculty ratios and the percentage of full-time faculty were not significant predictors for student retention. Some institutional predictor variables may be significant predictors for both retention rates and graduation rates, while other predictor variables may be significant predictors for only one of the criterion variables.
43

Achieving Stakeholder Buy-In for Student Engagement in Higher Education: Fostering Campus Climate Grounded in Student and Institutional Voices

Nakonechnyi, Alexei 22 October 2020 (has links)
No description available.
44

Riding Out the Waves: Community College Transfers Graduating with Bachelor's Degrees

Rice, Tamara Jean 09 April 2008 (has links)
No description available.
45

A Delphi Study: Exploring Saudi Faculty and Student Perceptions of the Factors Promoting Nursing Student Retention and Success

Alharbi, Homood, Mr. 23 November 2015 (has links)
No description available.
46

Undergraduate Student Perceptions of Service Quality as a Predictor of Student Retention in the First Two Years

Sickler, Stephanie L. 20 December 2013 (has links)
No description available.
47

Retaining Interests: The Relationship between Student Interests and Student Retention

Sabo, Melody 13 May 2016 (has links)
No description available.
48

Factors Affecting Student Retention At a Midsized Private University

McPherson, Gary Rynell 29 June 2016 (has links)
No description available.
49

A Model to Predict Ohio University Student Attrition from Admissions and Involvement Data

Roth, Sadie E. 05 August 2008 (has links)
No description available.
50

Missing Data Imputation Method Comparison in Ohio University Student Retention Database

Hening, Dyah A. January 2009 (has links)
No description available.

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