Generating Class Datasets for Teaching Qualitative Data Analysis Course to Graduate Students

Abstract

Teaching Qualitative Data Analysis to graduate-level students requires experiential learning and hands-on approaches, but there is a paucity of qualitative datasets available for teaching purposes. Pedagogical literature has paid relatively little attention to best practices related to the use of datasets in qualitative data analysis courses. It is essential for course instructors to have more methods in their toolkits to effectively generate instructional qualitative datasets. This article outlines a blueprint for creation of instructional qualitative datasets, using four general principles: (1) research topic of interest to students and not requiring specialized knowledge; (2) short time frame and ease of data collection; (3) student engagement; and (4) protection of research participants. We consider examples of how these principles were applied to generate three different datasets and discuss pros and cons of each method. This article describes a flexible approach, allowing for easy generation of custom instructional datasets.