Emergent Coding and Topic Modeling: A Comparison of Two Qualitative Analysis Methods on Teacher Focus Group Data

Autor/inn/en	Miyaoka, Atsushi; Decker-Woodrow, Lauren; Hartman, Nancy; Booker, Barbara; Ottmar, Erin
Titel	Emergent Coding and Topic Modeling: A Comparison of Two Qualitative Analysis Methods on Teacher Focus Group Data
Quelle	22 (2023), S.1-9 (9 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Decker-Woodrow, Lauren) ORCID (Ottmar, Erin) Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
Schlagwörter	Coding; Models; Qualitative Research; Focus Groups; Data Collection; Data Analysis; Mathematics Teachers; Middle School Teachers; Technology Uses in Education; Learner Engagement; Interaction; Feedback (Response); Student Reaction; Mathematics Instruction; Educational Games + Suchen Sie Ihr Suchwort? Codierung; Programmierung; Analogiemodell; Qualitative Forschung; Data capture; Datensammlung; Auswertung; Mathematics; Teacher; Teachers; Mathematik; Lehrer; Lehrerin; Lehrende; Middle school; Middle schools; Mittelschule; Mittelstufenschule; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Interaktion; Schülerkritik; Mathematics lessons; Mathematikunterricht; Educational game; Lernspiel
Abstract	More than ever in the past, researchers have access to broad, educationally relevant text data from sources such as literature databases (e.g., ERIC), an open-ended response from online courses/surveys, online discussion forums, digital essays, and social media. These advances in data availability can dramatically increase the possibilities for discovering new patterns in the data and testing new theories through processing texts with emerging analytic techniques. In our study, we extended the application of Topic Modeling (TM) to data collected from focus groups within the context of a larger study. Specifically, we compared the results of emergent qualitative coding and TM. We found a high level of agreement between TM and emergent qualitative coding, suggesting TM is a viable method for coding focus group data when augmenting and validating manual qualitative coding. We also found that TM was ineffective in capturing more nuanced information than the qualitative coding was able to identify. This can be explained by two factors: (1) the word level tokenization we used in the study; and (2) variations in the terminology teachers used to identify the different technologies. Recommendations include additional data cleaning steps researchers should take and specifications within the topic modeling code when using topic modeling to analyze focus group data. (As Provided).
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01