An Empirical Investigation of Student Evaluations of Instruction - The Relative Importance of Factors

We analyzed over 100,000 student evaluations of instruction over four years in the college of business at a major public university. We found that the original instrument that was validated about 20 years ago is still valid, with factor analysis showing that the six underlying dimensions used in the instrument remained relatively intact. Also, we found that the relative importance of those six factors in the overall assessment of instruction changed over the past two decades, reflecting changes in the expectations of the current millennial generation of students. The results were consistent across four subgroups studied – Undergraduate Core, Undergraduate Non-Core, Graduate Core and Graduate Non-Core classes, with minor differences. Student Motivation (the instructor’s ability to motivate students) and grading/assignments (fairness and objectivity of grading practices) have superseded presentation ability in relative importance as indicators of overall teaching effectiveness. Our study has implications for teachers in terms of the appropriate areas to focus on for improving their teaching practices

Norming of Student Evaluations of Instruction: Impact of Non-Instructional Factors

We analyzed Student Evaluations of Instruction (SEIs) from about 6000 sections over four years representing over 100,000 students at Georgia State University\u27s Robinson College of Business, to look for factors other than instructional attributes that might have an impact on the scores. We looked at environmental factors like semester, time of day, location, and instructor attributes like gender, and rank. These were analyzed across four segments created by course level (graduate and undergraduate) and course type (core and non-core). We found that several of the factors had varying degrees of impact on overall evaluation of an instructor. Summer semester ratings were higher than in Spring, which were higher than those in Fall. Time of day and classroom location mattered, though not in a consistent way across the segments. Undergraduates rated female instructors higher, while graduates rated male instructors higher on average. Instructor rank mattered, with non-tenure track faculty generally outperforming others (although there were small variations in results)

A framework of revenue opportunity in hotel management - an optimal room allocation approach

With all the published research on hotel Revenue Management (RM), a framework to guide a comprehensive hotel RM is rare in the extant literature. This research proposes a complete revenue opportunity framework for applying a traditional revenue management model for controlling room inventories for hotels. We propose and describe the framework and the model in this paper. The finished research will use archived data from a major hotel chain and apply the framework for generating controls for managing hotel room inventories to maximize revenue

ASSESSMENT OF EVALUATION METHODS FOR BINARY CLASSIFICATION MODELING

A well-established literature exists examining the relative performances of statistical and non-statistical modeling techniques. However, little organized research attention has been given to the evaluation methods used to determine model and technique superiority. We compare and contrast models developed using these techniques, specifically examining their respective classification accuracy through three methods of evaluation – Classification Rates, The Kolmorgorov-Smirnov Test and ROC curves. As our results revealed, the selection of a ‘best ’ model is contingent on the chosen evaluation method. Consequently, analysts would be well served to develop an understanding of the circumstances under which each evaluation method should be utilized