College student employment has been increasing steadily for at least four decades. At present, approximately 80% of all college students are employed while completing their undergraduate education. Even among students under the age of 24 at 4-year colleges, more than 50% are employed during the school year. Although some general trends are suggested by empirical research completed to date, studies that evaluate student employment and higher education are at times inconsistent and even contradictory. Despite the high prevalence of student employment, no theoretical models have been developed to explain the relationship between employment and student outcomes. This article briefly reviews the student employment-higher education empirical literature. Possible reasons for inconsistencies are suggested, including challenges posed by methodological issues and the absence of theoretical conceptualization. Some concluding suggestions are offered for addressing these empirical challenges.

This study investigated the effects the demographic variables age, gender, and ethnicity and their interactions had on academic performance in online courses delivered by public two-year colleges in Kentucky. The study controlled for previous academic performance measured by cumulative grade point average (GPA). The study used a random sample (N ¼ 320) of all students who had enrolled in at least one online course delivered by the institutions of the Kentucky Community and Technical College System in the spring 2008 semester. A linear hierarchical multiple regression acting as ANCOVA served as the main analysis, with the order entry as follows: cumulative GPA; independent variables (age, gender, ethnicity); interaction vectors; and product vectors. Final course grade served as the dependent variable. The results of the analysis indicated that only cumulative GPA was a significant predictor, explaining approximately 40% of the variance of the final grade. Although differences in final grades were present among the variables age and ethnicity, these differences disappeared when controlling for cumulative GPA. Significance of the results and recommendations for future research are discussed.

Rude-Parkins for being a very supportive dissertation chair and mentor. Your tremendous guidance has made the dissertation process not nearly as overwhelming as it once seemed. • Dr. Thomas Reio Jr. for guiding me in my understanding of research methods and statistical procedures. Your meticulous reviews of my chapters have provided me with valuable feedback. • Dr. Mike Boyle, whose sound guidance I have sought many times throughout this doctoral program. Thank you for taking the time to listen and guide me through the past four and a half years.

No abstract

No abstract