In qualitative research, most methods follow an emergent design (data collection and analysis go hand in hand, the codes and categories could change over time) so it is important to keep track of the entire process. There is a counter argument in favour of CAQDAS as well.
ATLASTI CLOUD SOFTWARE
Becker argues that qualitative research requires a lot of inductive thinking - creating codes, generating meanings from statements, categorizing the codes and identifying patterns - and computer software can oversimplify this process, resulting in superficial and descriptive studies, devoid of theory development. His argument was that computer software will take away the creativity of the researcher. Bryant and Charmaz has pointed out that Glaser (‘The Discovery of Grounded Theory’, 1967, co-authored with Strauss) opposed the use of computer software in qualitative research. With this as the background, let me put forward the arguments for, and against the use of CAQDAS. So, the software is merely an organization tool, to document the process of drawing inferences from the data. So, the researcher has to draw meanings and inferences from the subtle statements or observations, which cannot be done by a software. In qualitative studies, however, the researcher him/herself is a research tool analysis is a process of describing the perspectives of participants using the data. The role of the researcher here is to only specify the model, and the variables. In quantitative, the main use of the software is to calculate different statistics which describe the data, and then to run any statistical model needed to answer the research question. The purpose of using software in qualitative research is diametrically opposite to that in the case of quantitative research. In this blog we will elaborate on the use of CAQDAS, using ATLAS.ti as an example. The three most commonly used CAQDAS are ATLAS.ti, MAXQDA and Nvivo. One can do coding manually, either on the printed page or on a word processor, or do coding with the help of Computer Assisted Qualitative Data Analysis Software (CAQDAS). The usual approach is to use codes, which extract meaning from the data and then categorize codes into themes and then derive results based on coding of the systematic data. CONTEXTĭifferent data types can be used for qualitative research - interview transcripts, observations, audio/video/pictures - and the researcher’s role is to draw inferences by following systematic methods. The blog also discusses the basic functionalities of the ATLAS.ti software. Learn more about our work through case studies.In this blog, Aditya and Bhuvana elaborate on the pros and cons of using software in qualitative data analysis. Act onĪct on expresses how, through our global insights and local experts, we help build strategies and deliver services and solutions that achieve tangible outcomes. Visit our country sites in the top navigation to learn more about our local teams. It reflects how we work side-by-side with you to co-create the future. You can emphasizes our client-first mindset and dedication to deliver value to your organization. Learn more in the CGI Voice of Our Clients section. It also highlights our industry and technology expertise, and the best practices we’ve built over more than four decades of serving client needs. Insights represents our deep knowledge of industry trends and your business and IT priorities.
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