ABSTRACT
Computer-Assisted Qualitative Data Analysis (CAQDAS) is becoming increasingly prevalent in the social and health sciences and an expected skill for many researchers. CAQDAS is much less structured than the use of quantitative analysis software. However, actual CAQDAS practices and challenges have been insufficiently studied, especially among graduate students. The study addresses this gap through analysis of 15 semi-structured interviews with graduate students from different fields in a Canadian university. Analysis was guided by concepts from the Technology Acceptance Model (TAM) and the CAQDAS Postgraduate Learning Model (CPLM). Findings suggest that graduate students held high expectations of the analytic affordances of CAQDAS, yet experienced significant challenges in actualizing those expectations, due to the perceived complexity of CAQDAS, coupled with insufficient training. In this context, students manifested two divergent modes of engagement in CAQDAS – focused or comprehensive – each of which entailed substantial implications for their education and practice as emerging qualitative researchers.
Acknowledgments
This work was supported by the Alma Mater Society of the University of British Columbia under the 2019–2020 Impact Grant
Disclosure statement
No potential conflict of interest was reported by the author.
Supplementary material (Appendix A and B)
Supplemental data for this article can be accessed here
Notes
1. For an overview of different CAQDAS packages, see this link: https://www.surrey.ac.uk/computer-assisted-qualitative-data-analysis/resources/choosing-appropriate-caqdas-package
2. When these theoretical constructs are employed in the article, they are italicized.
3. It is the first phase of a larger project; the second phase is predominantly quantitative.
Additional information
Notes on contributors
Amir Michalovich
Amir Michalovich is a PhD Candidate in the Department of Language and Literacy Education at the University of British Columbia. His dissertation research explores digital multimodal composition among refugee-background youth. He is also leading a mixed-methods research project mandated to explore the challenges, needs, and practices of graduate students conducting CAQDAS. His research and teaching explore digital multimodal composition, media literacy, qualitative data analysis, and classroom interaction.