This study was designed to investigate and analyze whether a community college foster economic growth in its service area and, more specifically, to analyze the economic development contributions of one rural Mississippi community college to its service area. The population under study consisted of business owners in the community college’s area, local elected officials, a targeted community college president and administrators, economic development planners, and the Mississippi Development Authority. 100 questionnaires were distributed; 48% of them were returned. Data were collected, arranged, and analyzed using descriptive, comparative, and correlational statistical tools. Additionally, a 5-point Likert scale was used to measure the community college’s economic contribution statements. Demographic information was collected. The following information was revealed: (a) 35% of the respondents were elected officials, 20% were community college board members, and 21% were administrators; (b) 73% of those responding were Caucasian; and (c) 40% of those responding had 21 years or more of academic experience. Results revealed that respondents believed that this particular community college made significant contributions to the overall economic development of its service area. Based upon research findings, the researcher recommends the following: (a) continued elaboration between lawmakers and community college leaders, (b) identification of the economic needs of their regions by community college leaders, (c) community colleges’ employment of an Economic Development Recruiter, and (d) the maintenance of business incubators. Additionally, the researcher recommends that more research is needed to determine how college administrators can increase enrollment and retrain displaced workers who are now students.

The purpose of this study is to determine how economic factors correlate with and have an effect on enrollment at community colleges and provide benchmark enrollment strategies for use by community colleges in the future. A cluster sampling of 22 branch campus locations at 9 community colleges in Mississippi and their respective counties was selected. The independent variables used were median household income, percentage of persons below the poverty level, and unemployment rates. A statistical correlation and regression was conducted to determine if economic factors (median household income, percentage of persons below the poverty level, and unemployment by county) had any correlation or an effect on the decrease or increase in enrollment at the respective community college campus. The correlation and statistical effect based on the regression model used demonstrated that median household income and poverty levels had the strongest correlation and the most statistically significant effect on community college enrollment in Mississippi. Unemployment had a very weak correlation and no statistically significant effect on the sample for community college enrollment for Mississippi during this period. There were some exceptions in which certain community college campuses and their respective county unemployment rates had a very high effect on enrollment for that specific campus and that specific period. There were 6 phone interviews conducted following the analysis of the datasets to determine any internal or external causes to enrollment decreases and increases during this period. 4 of the 6 colleges responded. Of the colleges that responded, 2 saw increases and 2 saw decreases. The predominant enrollment factor denoted by the interviewee was retention and cohesive interdepartmental focus toward recruitment, which resulted in increased enrollment. Of the colleges that saw decreases and were interviewed, it was noted that enrollment personnel were not prepared for the enrollment decrease and could have been. Target markets with higher income and lower poverty levels perform better during harsh periods of challenge for enrollment at community colleges. Increased retention and interdepartmental cohesion produces better preparation for challenging periods of declining enrollment.

In this educational study, the research problem was that each semester a variable number of community college students are unable to complete an introductory computer applications course at a community college in the state of Mississippi with a successful course letter grade. Course failure, or non-success, at the collegiate level is a negative event for students and is a factor that leads to high attrition but does not always receive much research (Haynes Stewart et al., 2011). The purpose of this study was to see if a relationship existed between ACT scores (i.e., English, reading, mathematics, science reasoning, and composite) and student success in a computer applications course at a Mississippi community college. The first research question examined to see if the ACT composite test score was a statistically significant predictor of success in a computer applications course at a Mississippi community college. The second research question studied the ACT sub scores in English, reading, mathematics, and science reasoning to see if they were statistically significant predictors of success in the same course. Demographics of the sample were gathered from a multi-campus Mississippi community college along with the ACT scores and final grade in the computer applications class of the sample. Descriptive statistics were run and reported on the demographic data while bivariate and multivariate logistic regressions were utilized to examine predictability of the ACT scores in relation to course final grade. The time period covered by this study was from fall 2010 through spring 2012 excluding the summer semesters. The study showed that while the ACT scores were excellent predictors of inclusion in the success category, the ACT scores did a very poor job of predicting non-success. The study concluded with a summary of the findings as well as limitations of the study. Also discussed were recommendations for practitioners and policy makers to include making the information available to students, teachers, advisors, and administration as an advisement tool when deciding to take the computer applications class. As well, recommendations for future research include treating withdrawals separately, examining multiple schools for differences, and increasing internal validity.