Two primary software choices are available for the analysis of the qualitative data obtained for the Title IV-E project: Dedoose and Microsoft Excel. Excel can be used for a thematic analysis of open-ended survey questions to make meaning from common themes as well as unique perspectives. This approach would allow for transferring text to the software, generating and highlighting codes, identifying patterns and organizing codes into themes, and analyzing the data. According to Raubenheimer (2017), the advantages of using Excel include its accessibility and various display techniques for identifying, sorting, filtering, and organizing the data, which are helpful when doing a thematic analysis. Furthermore, the sections of the analysis can be easily copied and pasted into research articles and presentations. At the same time, Excel is not designed explicitly for thematic analysis, and the main disadvantages of using this software are its time-consuming nature and the inability to assign code to the text quickly.
Alternatively, Dedoose software, specifically designed for qualitative and mixed research methods, can be used to process the parent survey data. In particular, data must be imported, descriptor sets must be added, and codes must be created for further data analysis. As stated by Salmona et al. (2019), the significant advantages of processing data with Dedoose include the code description and management features that can help organize the ideas neatly and efficiently, which is critical for a considerable amount of data. Furthermore, the ability to generate multiple codes per answer would allow for a comprehensive view of the problem. The disadvantages of Dedoose are its cost in the long run once the free month trial expires and the need for internet connection since it is web-based. Apart from the possible technical issues, Dedoose software is suitable for meeting the desired results of the Title IV-E project. In turn, using Microsoft Excel can be laborious but helpful for sorting, filtering, and organizing the data for a comprehensive perspective.
References
Raubenheimer, J. (2017). Excel-lence in data visualization?: The use of Microsoft Excel for data visualization and the analysis of big data. In T. Prodromou (Ed.), Data visualization and statistical literacy for open and big data (pp. 153-193). IGI Global.
Salmona, M., Lieber, E., & Kaczynski, D. (2019). Qualitative and mixed methods data analysis using Dedoose: A practical approach for research across the social sciences. Sage Publications.