To Rod, my time as your graduate assistant was a tremendously rewarding experience but even more satisfying were the countless hours spent in your office conversing. It was during one of those conversations with Rod that the idea to explore student course evaluations was born.To Bob, I want to thank you for your support and for believing in the merit of this research, without which I would not have been able to conduct my study. I must also thank you and your research staff for dedicating innumerable hours to procuring and deidentifying data. Becky Patterson and Arnold Hook were tremendous assets and must be commended for their work in linking and mining the data that were analyzed in my study.To Joe, thank you for believing in me when I came to you as a student in counseling psychology and asked for admission into the ELFH program. Your extensive knowledge of student course evaluations, in particular the instrument used in the current study, was a great resource. concerning the instructor's teaching ability, preparation, grading, the course text and organization to which the student rates their agreement with the statement on a 5 point Likert-type scale ranging from 1 "Strongly Disagree", "Poor", or "Very Low" to 5 "Strongly Agree", "Excellent" or "Very High".In order to assess the relationship between the student, course, and instructor-level variables and the student course rating, hierarchical linear modeling (HLM) analyses were conducted. Most of the variability in student course rating was estimated at the student-level and this was reflected in the fact that most of the statistically significant relationships were found at the student-level. Prior student course interest and the amount v of student effort were statistically significant predictors of student course rating in all of the regression models. These findings were supported by previous studies and provide further evidence of such relationships.Additional HLM analyses were conducted to assess the relationship between student course rating and final course grade. Results of the HLM analyses indicated that student course rating was a statistically significant predictor of student course grade. This finding is consistent with the existing literature which posits a weak positive relationship between expected course grade and student course rating.vi