Beyond Average Information: How Q-Methodology Enhances Course Evaluations in Anatomy

Autor/inn/en	Brewer-Deluce, Danielle; Sharma, Bhanu; Akhtar-Danesh, Noori; Jackson, Thomas; Wainman, Bruce C.
Titel	Beyond Average Information: How Q-Methodology Enhances Course Evaluations in Anatomy
Quelle	In: Anatomical Sciences Education, 13 (2020) 2, S.137-148 (12 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Brewer-Deluce, Danielle) ORCID (Wainman, Bruce C.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1935-9772
DOI	10.1002/ase.1885
Schlagwörter	Anatomy; Q Methodology; Course Evaluation; Values; Student Attitudes; Preferences; Evaluation Methods; Student Diversity; Undergraduate Students + Suchen Sie Ihr Suchwort? Anatomie; Wertbegriff; Schülerverhalten
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 article 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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2022/1/01