Improving outcomes with Qualitative Data Analysis Software: A reflective journey

2017 ◽  
Vol 18 (3) ◽  
pp. 436-442 ◽  
Author(s):  
Austin G Oswald
Keyword(s):  
Qualitative Research ◽  
Social Work ◽  
Data Analysis ◽  
Qualitative Data ◽  
Research Process ◽  
Digital Tools ◽  
Analysis Software ◽  
Qualitative Data Analysis ◽  
Social Work Research ◽  
Qualitative Data Analysis Software

Now more than ever, qualitative social work researchers are being called upon to conduct increasingly complex, multifaceted, and intersectional research. Given the heightened complexity of social work research, it is necessary that scholars learn strategies to streamline the research process and digital tools for qualitative research are a mechanism to do so. In this paper, I share insights gleaned from personal experience working with Qualitative Data Analysis Software, specifically MAXQDA 12, to support a larger study that explored the social lives of older gay men. This paper highlights the various functions of MAXQDA 12 and how qualitative social work researchers can use the program to improve the research process and outcomes. Despite the rapid growth in production of digital tools for qualitative research there remains a dearth in studies that explicitly address how digital tools are used in the extant literature on qualitative research. This paper sheds light on this noted gap in the literature by exploring the functionality of MAXQDA 12 and how it can be applied to improve qualitative social work research.

scholarly journals Structuring a Team-Based Approach to Coding Qualitative Data

2020 ◽  
Vol 19 ◽  
pp. 160940692096870
Author(s):  
Lindsay Giesen ◽  
Allison Roeser
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Reference Materials ◽  
Qualitative Data ◽  
Research Process ◽  
Lessons Learned ◽  
Analysis Software ◽  
Management Structure ◽  
Qualitative Data Analysis Software ◽  
Supportive Management

Improvements to qualitative data analysis software (QDAS) have both facilitated and complicated the qualitative research process. This technology allows us to work with a greater volume of data than ever before, but the increased volume of data frequently requires a large team to process and code. This paper presents insights on how to successfully structure and manage a team of staff in coding qualitative data. We draw on our experience in team-based coding of 154 interview transcripts for a study of school meal programs. The team consisted of four coders, three senior reviewers, and a lead analyst and external qualitative methodologist who shepherded the coding process together. Lessons learned from this study include: 1) establish a strong and supportive management structure; 2) build skills gradually by breaking training and coding into “bite-sized” pieces; and 3) develop detailed reference materials to guide your coding team.

Building Transparency and Trustworthiness in Inductive Research Through Computer-Aided Qualitative Data Analysis Software

2019 ◽  
Vol 24 (1) ◽  
pp. 104-139 ◽  
Author(s):  
Paula O’Kane ◽  
Anne Smith ◽  
Michael P. Lerman
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Data ◽  
Building Blocks ◽  
Analysis Software ◽  
Qualitative Data Analysis ◽  
Inductive Research ◽  
Computer Aided ◽  
Qualitative Data Analysis Software ◽  
Data Analysis Software

Many scholars have called for qualitative research to demonstrate transparency and trustworthiness in the data analysis process. Yet these processes, particularly within inductive research, often remain shrouded in mystery. We suggest that computer-aided/assisted qualitative data analysis software (CAQDAS) can support qualitative researchers in their efforts to present their analysis and findings in a transparent way, thus enhancing trustworthiness. To this end, we propose, describe, and illustrate working examples of six CAQDAS building blocks, three combined CAQDAS techniques, and two coder consistency checks. We argue that these techniques give researchers the language to write about their methods and findings in a transparent manner and that their appropriate use enhances a research project’s trustworthiness. Specific CAQDAS techniques are rarely discussed across an array of inductive research processes. Thus, we see this article as the beginning of a conversation about the utility of CAQDAS to support inductive qualitative research.

scholarly journals Audiovisual Media Annotation Using Qualitative Data Analysis Software: A Comparative Analysis

2018 ◽  
Author(s):  
Liliana Melgar Estrada ◽  
Marijn Koolen
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Data ◽  
Information Science ◽  
Analysis Software ◽  
Qualitative Data Analysis ◽  
Audiovisual Media ◽  
Media Annotation ◽  
Qualitative Data Analysis Software ◽  
Data Analysis Software

The variety of specialized tools designed to facilitate analysis of audio-visual (AV) media are useful not only to media scholars and oral historians but to other researchers as well. Both Qualitative Data Analysis Software (QDAS) packages and dedicated systems created for specific disciplines, such as linguistics, can be used for this purpose. Software proliferation challenges researchers to make informed choices about which package will be most useful for their project. This paper aims to present an information science perspective of the scholarly use of tools in qualitative research of audio-visual sources. It provides a baseline of affordances based on functionalities with the goal of making the types of research tasks that they support more explicit (e.g., transcribing, segmenting, coding, linking, and commenting on data). We look closely at how these functionalities relate to each other, and at how system design influences research tasks.

scholarly journals Technology Ethics in Qualitative Research: How to Be

2019 ◽  
Author(s):  
António Costa ◽  
António Moreira
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Data ◽  
Special Edition ◽  
Analysis Software ◽  
Qualitative Data Analysis ◽  
Research Activity ◽  
Introductory Note ◽  
Qualitative Data Analysis Software ◽  
Data Analysis Software

This introductory note stems from the organization of a special edition of articles from the World Conference on Qualitative Research. Some researchers put forth criticisms about using software in qualitative data analysis, such as losing control in the coding process and leading researchers to use a particular method of analysis according to tool characteristics. Moreover, a number of the scientists believe that the advantages of using specific tools in data analysis are numerous, such as the analysis of an enormous amounts of data, but doing research involves personal or institutional aspects that enter the field of ethics. In the case of specific qualitative data analysis software, it would be possible to list a set of principles that would begin with the organization and importing of data, proceed with their interpretative and descriptive codification followed by questioning the data, up to exporting results to their written dissemination. Such principles could set the boundaries or define ethics in the use of software, referring to any research activity that touches what is right or wrong, good or bad, moral or immoral. This text is in line with the belief shared by others that work studies that can be performed on computational ethics will influence not only the use of Qualitative Data Analysis software but also their development.

Qualitative Data Analysis Software Practices in Complex Research Teams: Troubling the Assumptions About Transparency and Portability

2017 ◽  
Vol 23 (10) ◽  
pp. 779-788 ◽  
Author(s):  
Judith Davidson ◽  
Shanna Thompson ◽  
Andrew Harris
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Data ◽  
Analysis Software ◽  
Qualitative Data Analysis ◽  
Extensive Experience ◽  
Research Teams ◽  
Qualitative Data Analysis Software ◽  
Data Analysis Software

Early hypotheses about the ways Qualitative Data Analysis Software (QDAS) would be integrated into qualitative research lacked the backing of extensive experience. Changing contexts, such as the increasing use of complex teams, raise issues that bring into question earlier assumptions about the role of QDAS in transparency and portability. Using Jackson’s (2014) conception of transparency in motion as a grounding concept, the authors present an exemplar case of the ways one complex qualitative research team made use of QDAS to support interpretive activities in a project that was also geographically far flung. The article concludes with a reconsideration of the notion of transparency, suggesting a more nuanced approach for the future.

scholarly journals O USO DE PROGRAMAS DE COMPUTADOR NA ANÁLISE QUALITATIVA: OPORTUNIDADES, VANTAGENS E DESVANTAGENS.

2007 ◽  
Vol 12 (2) ◽  
pp. 56 ◽  
Author(s):  
Daniel Augusto Moreira
Keyword(s):  
Qualitative Research ◽  
Grounded Theory ◽  
Data Analysis ◽  
Data Storage ◽  
Qualitative Data ◽  
Computer Software ◽  
Analysis Software ◽  
Qualitative Data Analysis ◽  
Qualitative Data Analysis Software ◽  
Data Analysis Software

Qualitative Data Analysis Software is not extensively used in Brazil; also, misconceptions about qualitative research are still common. This study presents the main functions of Qualitative Data Analysis Software or, more properly, CAQDAS - Computer Aided Qualitative Data Analysis Software, as it is well known in the academic world. The relationship of CAQDAS with grounded theory is stressed, and so is text coding, as the central operational issue in grounded theory. Vantages and advantages of using software packages are analyzed. However their huge potential for facilitating data storage, manipulation and retrieval, their use is not always necessary or even recommended. As the packages are not neutral concerning theory, the analyst has to decide if and when to use a computer program and, if the package is in order, which one to use. Key words: Data analysis. Computer software. Qualitative research.

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