Abstracts, Oral, and Symposia Presentation for Qualitative Methods Conference, 2018 - Data analysis types in education through the use of software: The webQDA case

Abstract

The analysis of qualitative data in education tracks different paths, exploring various techniques, such as content analysis, discourse analysis, thematic, and narrative analysis. On the other hand, the use of Computer Assisted Qualitative Data AnalysiS has been increasing in terms of demand but also in the solutions available to researchers. The current scenario places these tools as essential, not only because they provide accuracy and systematization to research projects but also allow to reach results that otherwise wouldn’t be possible. In this context, software packages incorporate features that allow them to adapt to different techniques of analysis. In this study, we aim at understanding the pathways that researchers in education follow when using qualitative analysis software. To that end, we applied a questionnaire survey and conducted evaluation workshops for webQDA users—www.webqda.net (Souza, Costa, & Moreira, 2016)—in the area of Education. Results indicate that the most used technique is Content Analysis. Considering the steps defined in the e-book “Content Analysis in seven steps with webQDA” (Costa & Amado, 2017), most users don’t explore all the proposed steps, staying with the interpretive/inferential coding. We conclude that there is no knowledge or concern in the search for patterns, which can be achieved, for example, through the creation of “Matrices.” Although the technique most applied by users of webQDA in Education is Content Analysis, in the open answers (analyzed using webQDA), respondents propose functionalities that also allow exploring other techniques, such as social network and sentiment analysis.