Many educational institutions are using predictive models to leverage actionable insights using student data and drive student success. A common task has been predicting students at risk of dropping out for the necessary interventions to be made. However, issues of discrimination by these predictive models based on protected attributes of students…

The importance of retention rate for higher education institutions has encouraged data analysts to present various methods to predict at-risk students. Their objective is to provide timely information that may enable educators to channel the most effective remedial treatments towards precisely targeted students in an efficient manner. The present…

Analyses of student data in post-secondary education should be sensitive to the fact that there are many different topics of study. These different areas will interest different kinds of students, and entail different experiences and learning activities. However, it can be challenging to identify the distinct academic themes that students might…

Understanding large-scale patterns in student course enrollment is a problem of great interest to university administrators and educational researchers. Yet important decisions are often made without a good quantitative framework of the process underlying student choices. We propose a probabilistic approach to modelling course enrollment…

Depressive symptoms, a lack of close supportive relationships and suicidal ideation are important risk factors for suicidal acts. Previous studies have primarily focused on the additive effects of close relationships and depressive symptoms on suicide risk. Here we explored whether, in addition, close relationships moderated the impact of…

With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…

Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…

In an effort to improve developmental education students' outcomes, community colleges have been experimenting with acceleration strategies. Models of acceleration allow students to complete their developmental requirements in a shorter amount of time. However, there has been limited empirical research on the effects of accelerating students'…

Using the Health Belief Model as a conceptual framework, this study examined university students who may seek access to healthcare through an on-campus student clinic for screening and treatment of sexually transmitted infections. A cross-sectional research design was used to collect data from students enrolled in a general health education…

This exploratory study determined which set of student characteristics and disability-related services explained graduation success among college students with disabilities. The archived records of 1,289 unidentified students with disabilities in three public universities were examined ex-post-facto to collect demographic data on the students, the…

This study sought to better understand the early integration experiences of college students with disabilities by examining two research questions: (1) How well do the variables in Tinto's (1993) classic model of student attrition predict the early integration experiences of college students with disabilities? and (2) How do students with…

This study examines if and how holistic, person-centered academic advising, based on an integrative framework of educational psychology (Bronfenbrenner), sociology (Weber), and counseling (Rogers) theories, can be fostered, implemented, and assessed at a research university. The study design uses the coding of qualitative data and its translation…

This chapter presents a sophisticated approach for tracking student cohorts from entry through departure within an institution. It describes how a researcher can create a student tracking model to perform longitudinal research on student cohorts. (Contains 3 tables and 2 figures.)

As the growth of online programs continues to rapidly accelerate, concern over retention is increasing. Models for understanding student persistence in the face-to-face environment are well established, however, the many of the variables in these constructs are not present in the online environment or they manifest in significantly different ways.…

The nontraditional degree program at the University of Minnesota is located in a traditional setting, but the participants are exempted from many of the standard graduation criteria such as fulfillment of language and distribution requirements. Students' academic success is outlined along with the results of the study (evaluated by using…