First-year student retention: MAP-Works[superscript]TM early warning and intervention relationships

Abstract

This study investigated the use of the MAP-Works[superscript]TM program that is designed to help retain first-year students by identifying the level of retention risk for each student early in their first semester and communicating this risk to key university faculty and staff. The participants for this study were all first semester freshman students enrolled during the academic years 2012 and 2013. This study sought to determine if the MAP-Works[superscript]TM program and resulting intervention were effective in predicting the retention of high-risk first semester freshman students to their second semester and second year. The data analysis for this study used quantitative data analysis methods. The first and second research questions asking which of the factors were significant in predicting retention were answered using independent samples t-tests. The third research question asking if the intervention was significant was answered using a 2x2 Chi-square test for independence. The fourth and final research question asked which of the factors contributed the most in predicting retention was answered using a direct (binary) logistic regression analysis. This study found for high-risk domestic students Cumulative GPA, Socio-Emotional, Test Anxiety, Peers, Homesickness: Distressed, Academic Integration, Social Integration and Environment were able to be associated significantly with retention from fall-to-spring semester. For international students GPA, Self-Efficacy and Self-Discipline were able to be associated significantly with retention. The study showed for fall-to-fall retention for domestic students that cumulative GPA, Socio-Emotional, Communication, Analytical, Social Integration and On-Campus Living Social were significant. The research found that the intervention conducted by their direct connects for high-risk domestic students was significant for fall-to-fall retention. The logistic regression analysis showed for domestic students that Cumulative GPA, Financial Means, Socio-Emotional, and ACT Composite score were significant for fall-to-fall retention. The strongest predictor of retention was Cumulative GPA followed by Socio-Emotional, Financial then ACT Composite score. The regression analysis for high-risk international students showed that Cumulative GPA, Gender, and Student Residence were significant for fall-to-fall retention. The strongest predictor of retention was cumulative GPA, Gender (Female) and Student Residence (Off Campus).