Tonight I watched Dr. Eli Lieber’s webinar on quantitative descriptors and using Dedoose for data analysis. We’ve been using Dedoose for almost two years. I want to learn how to use some of the analysis tools. This session was recorded on July 8, 2024. The dataset used for the webinar was the QDAS Adoption Project. Lieber spoke about the types of descriptor data and research questions. Descriptors in Dedoose help build a web of data connections, explained Lieber. Descriptors can be organized in spreadsheets. Descriptors can be nested: several participants can be from the same institution, for example. Lieber explained that codes and descriptors are then used to explore data. The Technology Readiness Index scale was plotted with Dedoose for this dataset. Segmentation can be changed with the slider in Dedoose. T-tests can be conducted. Correlation scatter plots can be graphed. Lieber shared how descriptors are connected to the relevant excerpts. I thought the discussion about fear of QDAS from the survey data was really interesting and relatable. Code weights and dynamic descriptors can be used. Activating and filtering descriptors is a good way of limiting or including subsets.
