Maintaining and cultivating student engagement is critical for learning. Understanding factors affecting student engagement can help in designing better courses and improving student retention. The large number of participants in massive open online courses (MOOCs) and data collected from their interactions on the MOOC open up avenues for studying…

Educational institutions increasingly recognize the role that student belonging plays in retention. Many studies in this area focus on helping students improve a sense of belonging before they matriculate or identifying belonging as a reason for their departure. This study measures students' sense of belonging at key transition points during the…

Purpose: The purpose of this case study was to determine the impact of utilizing predictive modeling to improve successful course completion rates for at-risk students at California community colleges. A secondary purpose of the study was to identify factors of predictive modeling that have the most importance for improving successful course…

Online education continues to become an increasingly prominent part of higher education, but many students struggle in distance courses. For this reason, there has been considerable interest in predicting which students will succeed in online courses and which will receive poor grades or drop out prior to completion. Effective intervention depends…

Many researchers have explored the relationships between the likelihood of graduating from college and demographic and pre-college factors such as gender, race/ethnicity, high school grade point average (GPA), and standardized test scores. However, additional factors such as a student's college major, home address, or use of learning support in…

Retention is a complex issue of great importance to community colleges. Several retention models have been developed to help explain this phenomenon. However, these models typically have used four-year college and university environments to build their foundations. Several researchers have attempted to identify predictor variables using…

Every year a group of graduates from high schools enter the engineering programs across this country with remarkable academic record. However, as reported in numerous studies, the number of students switching out of engineering majors continues to be an important issue. Previous studies have suggested various factors as predictors for student…

The annual Student Outcomes Survey collects information on the outcomes of two groups of students--those that have completed a qualification (graduates) and those that have completed only part of a course and then left the vocational education and training (VET) system (module completers). At the time of selecting the survey sample, insufficient…

This study was designed to investigate the factors that affect master's student persistence in the United States. More specifically, this study explored whether the following factors: students' background, institution's, academic, environmental and psychological influences, had a significant effect on whether a master's student persisted and/or…

In an effort to standardize academic risk assessment, the NCAA developed the graduation risk overview (GRO) model. Although this model was designed to assess graduation risk, its ability to predict grade-point average (GPA) remained unknown. Therefore, 134 individual risk assessments were made to determine GRO model effectiveness in the…

This article describes the early outcomes of an ongoing project at the University of South Florida in Tampa that involves using a logistics regression formula derived from pre-matriculation characteristics to predict the risk of individual student attrition. In this piece, the authors will describe the results of the prediction formula and the…

The increasing competition for graduate students among business schools has resulted in a greater emphasis on graduate business student retention. In an effort to address this issue, the current article uses survival analysis, decision trees and TreeNet® to identify factors that can be used to identify students who are at risk of dropping out of a…

A model for predicting student credit hours (SCH) over a 2-year period was developed at the University of South Florida. A major application of the model would be to estimate the expected loss of upper-level SCH that would occur as a result of reduced lower-level enrollment. Attention was focused on the long-range effect of lower-level enrollment…

Virtual schooling has the potential to offer K-12 students increased access to educational opportunities not available locally, but comparatively high dropout rates continue to be a problem, especially for the underserved students most in need of these opportunities. Creating and using prediction models to identify at-risk virtual learners, long a…

This paper explores the need for a better understanding of the influences of prices and student aid on student enrollment and college budgets. The theory of net price has not been found to adequately explain changes in enrollment. Based on a critical review of recent research on student price response, this paper develops an alternative approach…