Completion of remedial mathematics has been identified as one of the keys to college success. However, completion rates in remedial mathematics have been low and are of much debate across America. This study leverages machine learning techniques in trying to predict and understand completion rates in remedial mathematics. The purpose of this study…

This longitudinal study evaluated the efficacy of a summer bridge program (SBP) and other support services on college graduation rates at a small liberal arts school in Purchase, NY. Financially disadvantaged students (n = 136) receiving a scholarship and a summer bridge curriculum within the Manhattanville Achievement Program were compared to…

This study examined graduation and persistence among social and behavioral science students at a regional comprehensive university. Hazard analyses identified predictors of student trajectories, times at which predictors were more or less impactful, and interactions between predictors such that particular risk factors were more detrimental for…

Research has shown that academic momentum is a key factor in degree completion for students attending 4-year institutions. The characteristics of 2-year students (also called community college students) often lead them to engage in behaviors contrary to the theory of academic momentum, and these behaviors theoretically reduce their likelihood of…

In this study, we identified factors influencing completion rates (graduation) of undergraduate students in science, technology, engineering, and mathematics (STEM). We used hierarchical, logistic, and linear regression models to analyze the data and found significant predictor variable interactions across various underrepresented versus…

This study assessed the feasibility of using precollege success indicators to identify at-risk students at a large 4-year public research university in the Midwest. Retention data from students who participated in an established student success program were examined. The findings affirm that the initial admissions assessment identifying at-risk…

Students are most likely to leave science, technology, engineering, and mathematics (STEM) majors during their first year of college. We developed an analytic approach using random forests to identify at-risk students. This method is deployable midway through the first semester and accounts for academic preparation, early engagement in university…

First-generation (FG) students are generally less likely than their continuing-generation (CG) peers to persist and complete a degree. Using student data available at initial enrollment, this multi-institutional study examines retention and transfer at the second year in relation to academic readiness, financial resources, college intentions,…

The present study examines the outcomes of a 5-week summer bridge writing program at a Midwestern, urban, public university designed to provide remedial instruction for incoming first-year college students, approximately 500 students annually for 7 years. Regression results showed that program participation was a positive, significant predictor on…

The purpose of the studies reported here was to test the hypothesis that college students from cultures that emphasize strong family ties experience familial tethering or a pull to remain connected to home, which then has negative consequences on the student's ability to connect to and succeed at the university. In Study 1, it was found that…

Violence against university students has significant impact on their mental health. The impact of violence on students' academic performance has received little attention. The primary purpose of this study is to examine the impact of sexual and physical/verbal violence on the academic performance of college students. Data from 74 case files of…

The current study explored the differential influences that behavioral learning strategies (i.e., cognitive-metacognitive, resource management), motivational profiles, and academic anxiety appraisals have on college-level learners in two unique learning contexts. Using multivariate analysis of variance and discriminant analysis, the study first…

Retention research rarely differentiates between students dismissed from an institution for poor academic performance versus students leaving by choice. As a proxy for studying academic dismissal, this study investigated differences between students leaving college in academic jeopardy after the first year (<2.00 grade point average) and those…

Two approaches, Linear Discriminant Analysis, and Logistic Regression are used and compared to predict success or failure for first-time freshmen in the first calculus course at a medium-sized public, 4-year institution prior to Fall registration. The predictor variables are high school GPA, the number, and GPA's of college prep mathematics…

A plethora of research spanning several decades has attempted to understand predictors of retention and graduation in undergraduate bachelor's degree programs. The topic is no less important today, as larger and larger swaths of the American population attend college each year. Studies have demonstrated that key demographic variables, indicators…