Bringing them back: using latent class analysis to re-engage college stop-outs

Area of Science:

• Higher Education Research
• Educational Psychology
• Sociology of Education

Background:

• * Over 50% of students entering college do not complete a degree or certificate.
• * Factors like low socioeconomic status (SES), being first-generation, academic performance, and financial difficulties impede degree completion.
• * Stopping out may indicate barriers rather than a lack of interest in education.

Purpose of the Study:

• * To explore subgroups of college seniors who stopped out before graduation using person-centered statistical methods.
• * To identify distinct latent classes of students based on demographic, academic, and financial variables.
• * To inform institutional strategies for re-engaging students and allocating resources effectively.

Main Methods:

• * Latent Class Analysis (LCA) was applied to a dataset of students who stopped out.
• * The analysis utilized demographic, academic, and financial variables.
• * A six-class model was determined to be the best fit for the data.

Main Results:

• * Latent Class Analysis identified six distinct subgroups of students who stopped out.
• * Academic and financial variables were significant determinants of these latent classes.
• * The findings highlight specific profiles of students facing barriers to degree completion.

Conclusions:

• * Identifying student subgroups through LCA can aid institutions in developing targeted interventions.
• * Understanding the key academic and financial drivers of stopping out is crucial for student retention.
• * Person-centered approaches can improve re-engagement strategies and optimize resource allocation for student success.