The Tail Wagging the Dog; An Overdue Examination of Student Teaching Evaluations

Abstract

Purpose: The purpose of this research is to examine the impact of several factors beyond the professor's control and their unique impact on Student Teaching Evaluations (STEs). The present research pulls together a substantial amount of data to statistically analyze several academic historical legends about just how vulnerable STEs are to the effects of: class size, course type, professor gender, and course grades.Design/methodology/approach: This research is utilizes over 30,000 individual student evaluations of 255 professors, spanning six semesters, during a three year time period to test six hypotheses. The final sample represents 1057 classes ranging in size between 10 and 190 students. Each hypothesis is statistically analyzed, with either analysis of variance or a Regression model. Findings:This study finds support for 5 out of 6 hypotheses. Specifically, these data suggest STEs are likely to be closest to "5" (using a 1-5 scale with 5 being highest) in small elective classes, and lowest in large required classes taught by females. As well we find support for the notion that higher expected course grades may lead to higher STEs. Practical implications:The practical significance of this research is important. First this research utilized a large data set spanning several years and hundreds of professors and thousands of students and rigorous statistical analysis to assert several important findings. Indeed STEs are impacted significantly by class type, class size, the gender of the professor and the expected course grade. With these findings we suggest a more comprehensive mechanism is in order for evaluation of teaching effectiveness. Social implications:This research could have great social implications if widely read across academic circles. Indeed the tail is wagging the dog; or the student is influencing teaching across America's universities. It is time to examine teaching effectiveness through a different lens, because using teaching evaluations to determine promotion and tenure, sparse bonus allocation, and teaching awards may be short sighted. Research limitations:While this research is statistically accurate, it is limited by the notion that the data was collected from one large area. As such, care should be taken in generalizing these results to other areas that may have different demographic composition, funding etc. Originality/value:To the best of the authors' knowledge this research is the first of its kind to statistically analyze such a large body of data and provide a useful guide to help evaluate professors utilizing what information is available.

Transforming mentorship in STEM by training scientists to be better leaders

“…Effective mentoring can be difficult to measure as it involves both metrics of graduate student success (e.g., publishing papers, progress toward graduation), and less tangible metrics such as student mental health, support, and satisfaction. Additionally, evidence from research on teaching evaluations suggests that students can be biased when evaluating certain groups, such as women, and thus evaluations based on student opinion alone must be used with caution (Boring, ; Mengel, Zölitz, & Mengel, ; Miles & House, ; Stark & Freishtat, ; Storage, Horne, Cimpian, & Leslie, ). Finally, finding mechanisms that allow for honest feedback in academia is challenging, as graduate students and postdocs must be protected from retribution in cases of a negative review.…”

Student evaluations of teaching (SET): Guidelines for their use

“…Ratings should be completed anonymously without the teacher present and be standardized in administration (e.g., identical instructions, same time frame for administration) across all courses in the school. Individuals and committees interpreting the ratings should understand variables that might affect student evaluations such as motivation for taking the course, workload in the course, timing of the evaluations, level of the student and course, class size, and other variables . Too few faculty are knowledgeable about variables that can influence student ratings in their courses.…”

A Study of the Correlation of the Improvement of Teaching Evaluation Scores Based on Student Performance Grades

“…They hypothesize that when students expected they would get better grades, they would give teachers higher teaching evaluation scores. Miles and House (2015) examined the impact of factors that teachers can't control on teaching evaluation scores. The results found that higher student' expected grades may lead to higher teaching evaluation scores.…”