Brewer-Deluce, Danielle, Shanu Sharma, Noori Akhtar-Danesh, Thomas Jackson, & Bruce Wainman (2019, April, in press). Beyond average information: How Q‐methodology enhances course evaluations in anatomy. Anatomical Sciences Education. 12 pp. (ePub in advance of print) (doi: 10.1002/ase.1885) (Link:

Abstract: Course evaluations can be used for curriculum improvement and have the potential to better the student learning experience. However, because most are based on Likert‐scales and open‐ended feedback, understanding diversity in student opinion and uncovering optimal options for course change and improvement are often difficult. Alternatively, Q‐methodology can be used to investigate patterns of thought within a group and may offer greater potential for course reform. This manuscript offers a tutorial‐based explanation of the three components of Q‐methodology studies (1) survey instrument development, (2) data collection, and (3) analysis and interpretation, then demonstrates, via case‐study, the use of Q‐methodology to evaluate a fourth‐year undergraduate pathoanatomy course. The goal of this paper is to enable the reader to broadly apply Q‐methodology in other courses to gain insight and feedback beyond that offered by traditional Likert‐scale methods. As demonstrated through the pathoanatomy case study, Q‐methodology highlights groups (denoted by factors) of like‐minded students that share opinions, preferences and values. Overall, Q‐methodology analyses support course instructors in identifying areas of course strength and improvement in an evidence based‐way. This alternative to traditional Likert‐scales represents a promising solution to ongoing course evaluation limitations.

Danielle Brewer-Deluce <> is in the Education Program in Anatomy and Department of Kinesiology, McMaster University, Hamilton, Ontario, Canada.

Leave a Reply

Please log in using one of these methods to post your comment: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.