The Relationship of Scores on the Personal Background Preparation Survey and First Semester Educational Outcomes for Students at a Health Science Community College
MetadataShow full item record
Background: Graduation rates at community colleges who serve nontraditional and diverse student populations have remained critically low for many decades. Research studies have cited cognitive factors, such as a low level of academic preparation, as well as non-cognitive factors, such as a lack of money or family obligations, as causes for student failure and dropout. Early identification of students with medium or high-risk factors could help improve their graduation rates and ultimately reduce the shortages in many health care professions. Purpose: The purpose of this study was to measure the effectiveness of the Personal Background Preparation Survey (PBPS) in identifying at-risk students during their first semester in a health science program at a community college. The study answered the following research question, “What is the effectiveness of the PBPS in identifying at-risk students during their first semester at a community college?” Methods: This study used archival data collected during 2010 – 2015 under a grant between two southwestern U.S schools. The correlational design analyzed the predictor PBPS total risk scores that assessed the newly enrolled students’ initial risk levels, the presence versus absence of interventions, ethnicity, and gender using correlational design analyses. Correlation statistics using Spearman’s Rho were completed to determine if any correlation existed between the student’s risk level and their educational outcome. In addition, to further examine the data, chi-square analyses were done for educational outcomes based on the semester. Results: There were more women (78.8%) than men (21.2%) in the dataset. The most common racial/ethnic groups were Hispanic (29.2%), Black-African American (21.4%), and Asian (19.1%). The risk level for the students ranged from 1-10 (2.9%) to 41-50 (0.2%) with a median risk level of Mdn = 25.50. Eighty-one percent of the sample had positive educational outcomes, with another 10.7% being considered at risk, and the final 8.7% of the students had attrition. The Spearman correlation between the student’s risk level and their educational outcome showed a slight positive correlation (r s = .10; p<.05) and accounted for 1.0% of the shared variance between the two variables. Further evaluation using chi-square analysis between semesters and educational outcomes showed a statistically significant association between the students’ semester and their educational outcomes, χ2 (2) = 389.95, p = .001. The association was moderate (Cramer’s V = .49). Conclusion: The results of the study suggest that the self-report used by this urban community college does identify at-risk students in Other Racial/Ethnic Groups Only subsamples while other groups were slightly positive to weak. The study also revealed that as far as nonintervention versus intervention semesters, the rate of success of the intervention increased respectively by semesters and later semesters grouped together. If it is an academic institution’s wish to improve retention rates regarding at-risk students, they should begin a prescription plan that provides students the tools they need to foster an environment that leads to success.