Using QCAmap for Qualitative Content Analysis: A Tutorial with Simulated Teacher Interviews
Keywords:
QCAmap, Content Analysis, Qualitative Data AnaAbstract
Qualitative data analysis is often complex and requires the researcher’s meticulous attention in organizing, interpreting, and systematically summarizing data. QCAmap was developed as a tool for content analysis to assist with coding, decoding, and presenting analytical results derived from qualitative data. To demonstrate its practical application, this article presents a case study generated using ChatGPT, in which the author created a simulated scenario where a researcher interviews teachers who have recently been appointed during their first three years of work. The objective of this article is to introduce and demonstrate the step-by-step use of QCAmap for content analysis. It presents the initial setup and methodological framework leading to the development of categories, definitions, anchor examples, and coding rules, which are then used to decode interview data and display the results in a frequency table of categories and excerpts. The trial use of QCAmap reveals that the platform effectively manages textual data, is user-friendly, and supports the Thai language. Therefore, it is suitable for those interested in conducting qualitative content analysis and learning to use systematic analytical tools.
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Translated Thai References
Piromsombat, C. (2024). Advanced(?) content analysis: Known, yet misunderstood [Lecture notes]. Faculty of Education, Chulalongkorn University.
Piromsombat, C. (2025). Content analysis: Widely used, wildly misused [Lecture notes]. Faculty of Education, Chulalongkorn University.
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