Feedback from Western's Your Feedback Student Questionnaire on Courses and Teaching (SQCT) can be used to make decisions about courses and programming and is also considered in regular faculty review procedures, including promotion and tenure.
In any year, it is important to consider the context in which a course is taught. For example, new instructors, instructors teaching a course for the first time, or instructors who wish to try new teaching techniques or innovations may experience a fluctuation in ratings data and types of comments they receive. Such contexts must be kept in mind when reviewing SQCT feedback. In particular, instructors wishing to try innovative approaches to teaching or simply improve their teaching by trying out techniques that are new to them should not feel inhibited to do so because of a fear of lower SQCT ratings feedback (Havita, 2014).
In this transitional year, as we move the SQCT online, it is particularly important to remember that the numerical data is not meant to provide a final assessment of an instructor's teaching; it should be seen as a form of constructive feedback that provides insight into the ways in which students learn and interact with instructors and course materials, promoting conversation, reflection, and action. Combined with other indicators of instructional success, questionnaire numerical data constructs a wider "picture" of individual instruction at Western, while questionnaire comments provide a context for interpreting the numerical data.
While research indicates that response rates often drop when introducing an online SQCT, previous research has indicated there is no significant difference between the mean ratings scores on SQCTs administered online vs. in-class. In addition, while there is no statistical difference between the type of comments students provide (i.e., positive, negative, or neutral), students are more likely to leave longer and more thoughtful comments on online SQCTs (Stowell, Addison, & Smith, 2012; Venette, Sellnow, & McIntyre, 2010; Dommeyer, Baum, Hanna & Chapman, 2004).
Look at more than just the mean score. The mean score should be understood in relation to the median score and standard deviation. The mean score is the average of the rating responses for a single question. The median is the middle score of all of the ratings responses.
As an extreme example, in a class of 41 students, 33 students might rate the overall course experiences as 6 (very good), while 8 students might rate it as 1 (very poor). The mean (i.e., average) for overall course experience would be 5 (good), despite the fact that 80% of the students had a very good overall course experience.
The median is calculated by laying out all individual ratings for a question from low to high and choosing the score that is the middle number in that range. In this case, there were 41 responses, so a response of 6 (very good) would be the middle rating if all 41 responses were listed from low high. So, in this case a minimum of 50% of students believed the course experiences was at least "very good."
In both cases, it is important to know that 8 students felt the overall course experience was very poor, but the median shows that most students had a very good overall course experience.
Standard deviation is an indication of differences of ratings within student responses. A smaller standard deviation, (e.g., 1) indicates that students are generally in agreement in their responses, while a larger standard deviation (e.g., 3) indicates that student answers covered a larger range of ratings.
For example, if the question, "Overall, how would you rate this course as a learning experience" has a rating mean of 6 with a standard deviation of 0.5, students will be generally in more agreement with each other on this item than if the standard deviation was 1.5.
Deans have access to the Section 5 of the SQCT, which asks students to provide any supplementary comments about the course. These comments can provide useful feedback related to many aspects of course and degree programming, some of which instructors do not have control over, such as when courses are scheduled, class size and format, and repetition of content from other courses. This type of feedback is particularly helpful for faculties completing self-studies for the IQAP process, but can also serve as a source for ongoing data related to course programing, curriculum mapping, and variety of teaching approaches. Keep the following in mind when reviewing course comments:
Adams, C. M. (2012). On-line measures of student evaluation of instruction. In M. E. Kite (Ed.), Effective evaluation of teaching: A guide for faculty and administrators (pp. 50-59): Retrieved from the Society for the Teaching of Psychology website: http://teachpsych.org/ebooks/evals2012/index.php
Boysen, G. A. (2016). Statistical knowledge and the over-interpretation of student evaluations of teaching. Assessment & Evaluation in Higher Education. http://dx.doi.org/10.1080/02602938.2016.1227958
Boysen, G. A. (2015). "Uses and misuses of student evaluations of teaching: The interpretation of differences in teaching evaluation means irrespective of statistical information." Teaching of Psychology, 42(2), 109-118. http://dx.doi.org/10.1177/0098628315569922
Boysen, G. A., Kelly, T. J., Raesly, H. N., & Casner, R. W. (2014). "The (mis)interpretation of teaching evaluations by College faculty and administrators." Assessment and Evaluation in Higher Education 39(6), 641-656. http://dx.doi.org/10.1080/02602938.2013.860950
Dommeyer, C. J., Baum, P., Hanna, R. W., & Chapman, K. S. (2004). Gathering faculty teaching evaluations by in-class and online surveys: Their effects on response rates and evaluations. Assessment in Higher Education, 29(5), 611-623. http://dx.doi.org/10.1080/02602930410001689171
Havita, N. (2014). Student ratings of instruction: A practical approach to designing, operating, and reporting (2nd ed.). Oron Publication.
Stowell, J. R., Addison, W. E., & Smith, J. L. (2012). Comparison of online and classroom-based student evaluations of instruction. Assessment & Evaluation in Higher Education, 37(4), 465-473. http://dx.doi.org/10.1080/02602938.2010.545869
Theall, M., & Franklin, J. (1991). Using student ratings for teaching improvement. In M. Theall & J. Franklin (Eds.), Effective practices for improving teaching: New Directions for Teaching and Learning (pp. 83-96). San Francisco: Jossey-Bass.
Venette, S., Sellnow, D., & McIntyre, K. (2010). Charting new territory: Assessing the online frontier of student ratings of instruction. Assessment & Evaluation in Higher Education, 35(1), 97-111. http://dx.doi.org/10.1080/02602930802618336