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Rocconi, Louis M.; Gonyea, Robert M. – Research & Practice in Assessment, 2018
The concept of effect size plays a crucial role in assessment, institutional research, and scholarly inquiry, where it is common with large sample sizes to find small relationships that are statistically significant. This study examines the distribution of effect sizes from institutions that participated in the National Survey of Student…
Descriptors: College Freshmen, Learner Engagement, College Seniors, National Surveys
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Miller, Angie L.; Rocconi, Louis M.; Dumford, Amber D. – Higher Education: The International Journal of Higher Education Research, 2018
High-impact practices (HIPs) are important co-curricular educational experiences in post-secondary education, as they promote learning, development, and persistence among students. The goal of this study was to extend the research on HIPs to explore potential connections with HIP participation and career outcomes. Using data from the National…
Descriptors: College Seniors, Educational Practices, Education Work Relationship, Career Planning
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Rocconi, Louis M.; Ribera, Amy K.; Nelson Laird, Thomas F. – Research in Higher Education, 2015
This study examines the extent to which college seniors' plans for graduate school are related to their tendency to engage in deep approaches to learning (DAL) and their academic environments (majors) as classified by Holland type. Using data from the National Survey of Student Engagement, we analyzed responses from over 116,000 seniors attending…
Descriptors: College Seniors, Graduate Study, Student Educational Objectives, Academic Aspiration
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Rocconi, Louis M. – Higher Education: The International Journal of Higher Education and Educational Planning, 2013
This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student…
Descriptors: Hierarchical Linear Modeling, Least Squares Statistics, Regression (Statistics), Critical Thinking
Rocconi, Louis M. – Association for Institutional Research (NJ1), 2011
Hierarchical linear models (HLM) solve the problems associated with the unit of analysis problem such as misestimated standard errors, heterogeneity of regression and aggregation bias by modeling all levels of interest simultaneously. Hierarchical linear modeling resolves the problem of misestimated standard errors by incorporating a unique random…
Descriptors: Regression (Statistics), Models, Least Squares Statistics, Data Analysis