The Promises and Pitfalls of Using Student-Generated Data to Teach Deductive Qualitative Analysis

Bibliographic Data

ID12377729
AuthorsElizabeth Ralph-Morrow (0000-0002-8591-7197, University College London, corresponding author), Daniel Schulte (0009-0004-6149-1939, University College London), John-Paul Salter (0000-0001-8469-7914, University College London), Alexandra C Hartman (0000-0001-6847-3734, University College London)
Year2026
Volume59
Issue2
Pages352-358
Publication date2026-02-27
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenuePS Political Science & Politics (JOURNAL)
Journal identifiersISSN: 1049-0965 • E-ISSN: 1537-5935
PublisherCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/s1049096525101686
OpenAlexW7131800159
LanguageEN
References cited13

A specific challenge of qualitative methods teaching is including skills for both data generation and data analysis, with recent audits of political science curricula revealing that the latter is particularly neglected at the undergraduate level. There are few published discussions on the importance of teaching analytical mechanics or guidance provided on how best to find and use data for teaching. This article explains how we integrated an exercise that enabled our class of more than 100 undergraduate students to generate their own original data and then to practice deductive coding and analysis. In addition to discussing our teaching experiences, we draw on interviews with our students to reflect on the successes and challenges of our approach and to offer suggestions to other instructors who want to replicate our strategy in a large undergraduate setting

Audit · Best practice · Class (philosophy · Coding (social sciences · Curriculum · Qualitative analysis · Qualitative property · Qualitative research · Evaluation of Teaching Practices · Innovative Teaching Methodologies in Social Sciences · Statistics Education and Methodologies

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Open DOIOpen Access