Using large-scale longitudinal data, this study sought to examine factors influencing two important student development outcomes in students with disabilities attending 4-year colleges and universities. Informed by Astin's Input-Environment-Outcome model and the interactional model of disability, this study investigated the effect of student…

This study examines the relationships between the normative and resource dimensions of a high school counseling department and four-year college-going rates. Utilizing data from the High School Longitudinal Study of 2009 (HSLS: 09), we employ multiple regression and latent class analysis to identify salient factors related to the college-going…

Researchers have recently claimed that there are substantial differences in the psychosocial dispositions and academic achievement of male and female college students. To test this proposition, a sample of 854 undergraduate students were selected from a major Canadian Research-1 university. Multiple regression analyses assessed the effects of…

The concept of student engagement is receiving increased attention from researchers, higher education leaders, and the general public in recent years. This increased attention represents a shift from the more traditional "resource and reputation" model of academic quality to a model that emphasizes institutional best practices and student…

Data from the National Research Council's Doctorate Records File extract prepared for UCLA indicated that source of support was the most important variable in predicting time to doctorate. Following source of support were postdoctoral plans, number of dependents, sex, and field of study. (Author/MLW)

Academic dishonesty (cheating) has been prevalent on college campuses for decades, and the percentage of students reporting cheating varies by college major. This study, based on a survey of 643 undergraduate engineering majors at 11 institutions, used two parallel hierarchical multiple regression analyses to predict the frequency of cheating on…

To investigate how students' characteristics and experiences affect satisfaction, this study uses regression and decision tree analysis with the CHAID algorithm to analyze student-opinion data. A data mining approach identifies the specific aspects of students' university experience that most influence three measures of general satisfaction. The…

All teacher evaluation forms completed in the arts and sciences division of a large community college were analyzed. Multiple regression was used to predict teacher rating. Items relating to teacher characteristics as perceived by the students (e.g., "tries to help students understand," etc.) had a consistant impact on rating. (Author/MLW)

This study employed multiple linear regression and decision tree analysis to examine the correlates of overall satisfaction with undergraduate education for white, Asian American, Latino and African American seniors enrolled at 17 doctoral/research universities. Satisfaction with the overall quality of instruction and social involvement were the…