Making Sense of All the Words

Author(s):  
Janice E. Jones ◽  
A. J. Metz

This chapter provides an introduction to the process of qualitative analysis and to use step by step examples to provide an idea of how the process of qualitative analysis actually works. Crabtree and Miller, 1992, note that there are many different strategies for analysis, in fact, they suggest there are as many strategies as there are qualitative researchers. This chapter is intended to give the researcher a place to begin and to inspire a deeper dive into this rewarding form of data analysis. Stake, (1995) writes that qualitative data analysis is “a matter of giving meaning to first impressions as well as to final compilations. Analysis essentially means taking something apart. We take our impressions, our observations, apart… we need to take the new impression apart, giving meaning to the parts”(p. 71). While qualitative data analysis can be time consuming the rewards that come from immersion in the data far outweigh the time spent doing so.

2018 ◽  
Vol 25 (9-10) ◽  
pp. 1085-1090 ◽  
Author(s):  
Leo A. Mallette ◽  
Johnny Saldaña

The purpose of this article is to describe the use of a party game, adapted by the two authors, to teach qualitative data analysis in consulting and classroom settings. The value of this exercise lies in its narrative construction outcomes. Qualitative methodologists frequently advise students to find the story of their study, but that task is often elusive given the overwhelming magnitude of data collected, and research novices often have difficulty grasping basic principles of qualitative analysis. Games are metaphors for life, and the activity described here and other games reviewed in this article are metaphors for the disparate and sometimes idiosyncratic data we collect in the field, and how we must pattern, unify, and make interpretive sense of them by constructing plausible organizational arrays and interrelationships. Flavor bites and dialogue from the participants attest that these are positive and beneficial learning exercises.


2020 ◽  
Vol 27 (2) ◽  
pp. 505-530
Author(s):  
Hendi Yogi Prabowo

Purpose The purpose of this paper is to explore the potential of computer-assisted qualitative data analysis software (CAQDAS) to support qualitative evaluation of corruption prevention initiatives, especially those focusing on behavioral changes. To achieve this objective, this paper applies the principles of qualitative inquiries to establish a foundation for developing effective means for evaluating behavior-oriented corruption prevention initiatives in Indonesia. Design/methodology/approach Through exploratory study, this paper assesses current corruption prevention evaluation practice in the Indonesian public sector to highlight major deficiencies thereof primarily through examination of publicly available documents on anti-corruption practice in Indonesia. Furthermore, this paper also discusses how qualitative methods using CAQDAS may strengthen the existing anti-corruption regime by aiding decision-makers to better evaluate the success or failure of their corruption prevention initiatives in particular those aiming for behavioral changes. To illustrate how a qualitative data analysis application can support anti-corruption evaluators, NVivo will be used as a reference from which multiple analytical tools will be discussed to highlight their potential for qualitative qualitative analysis analysis in corruption prevention evaluation. Findings The author establishes that the existing quantitative measures of evaluation are insufficient in generating a comprehensive picture of the success or failure of the existing anti-corruption initiatives in Indonesia. Evidences suggest that the existing quantitative measures appear to be unable to cope with the growing complexity of various corruption problems in the country in particular to those related to organizational culture and behavior. Despite the numerous behavior-oriented initiatives to reduce the risk of corruption in the Indonesia public sector, it is still unclear if such initiatives actually have made a difference in preventing corruption, as many of their elements cannot be measured quantitatively. Therefore, the author believe that deeper insights into corruption problems can be obtained through proper qualitative assessments in which evaluators play the role as the primary analytical instrument. To enhance evaluators’ capability in obtaining and analyzing qualitative data, the author proposes the use of CAQDAS and the evaluation of corruption prevention initiatives. With a special reference to NVivo, the author argues that using CAQDAS will enable evaluators to conduct qualitative analysis more efficiently to identify patterns within the data, as it offers various tools to look deeper into context, diversity, nuance and process so as to gain deeper understanding of the meaning of human action and how it may affect the risk of corruption within organizations. Research limitations/implications This study is self-funded and is relying primarily on documentary analysis in assessing the existing corruption prevention evaluation measures in Indonesia. Future studies may benefit from in-depth interviews with anti-corruption evaluators in particular from the country’s anti-corruption agency. Practical implications This paper contributes to the development of corruption prevention strategy by proposing a framework for systematically performing qualitative evaluation on behavior-oriented corruption prevention initiatives. Originality/value This paper highlights the importance of qualitative measures in evaluating behavior-oriented corruption prevention initiatives in the Indonesian public sector.


Author(s):  
Ronald Chenail

In the second of a series of “how-to” essays on conducting qualitative data analysis, Ron Chenail argues the process can best be understood as a metaphoric process. From this orientation he suggests researchers follow Kenneth Burke’s notion of metaphor and see qualitative data analysis as the analyst systematically considering the “this-ness” of the data from the “that-ness” of the qualitative abstraction drawn about the data. To make this metaphoric pronouncement a convincing case to judges as to the veracity of the juxtaposition of the code to that which is coded, the analyst must employ a recursive process by showing the presence of the qualities of the unit of analysis in the product of the qualitative analysis as evidence of the quality of the analysis itself. This evidentially recursive act must be made overtly because in qualitative data analysis, the data do not speak for themselves.


Author(s):  
Neringa Kalpokaite ◽  
Ivana Radivojevic

Qualitative research is a rich and diverse discipline, yet novice qualitative researchers may struggle in discerning how to approach their qualitative data analysis among the plethora of possibilities. This paper presents a foundational model that facilitates a comprehensive yet manageable approach to qualitative data analysis, and it can be applied within an array of qualitative methodologies. Based on an exhaustive review of expert qualitative methodologists, along with our own experience of teaching qualitative research, this model synthesises commonly-used analytic strategies and methods that are likewise applicable to novice qualitative researchers. This foundational model consists of four iterative cycles: The Inspection Cycle, Coding Cycle, Categorisation Cycle, and Modelling Cycle, and memo-writing is inherent to the entire analysis process. Our goal is to offer a solid foundation from which novice qualitative researchers may begin familiarising themselves with the craft of qualitative research and continue discovering methods for making sense of qualitative data.


Author(s):  
Jessica Lester ◽  
Noah Goodman ◽  
Michelle O'Reilly

This article introduces the special issue, “Diverse Approaches to Qualitative Data Analysis for Applied Research,” in which seven papers analyze one shared data set to illustrate different approaches to qualitative analysis. In addition to discussing the articles included in the special issue, this introduction provides an overview of applied research—highlighting some of the implications for qualitative research—and discusses how researchers could use the special issue to compare different qualitative approaches to choose one most appropriate for a given project’s goals.


2021 ◽  
pp. 136078042110035
Author(s):  
Neringa Kalpokas ◽  
Ivana Radivojevic

The interpretative and flexible nature of qualitative research is one of its hallmark strengths, yet this can pose a significant obstacle for researchers who wish to incorporate computer-assisted qualitative data analysis software (CAQDAS), especially for educators of CAQDAS and researchers who may have abandoned CAQDAS following past frustrations. We seek to help qualitative researchers and teachers by illustrating how CAQDAS can be used to follow specific analytic strategies (e.g. inductive and deductive analysis, category identification and synthesis, and qualitative model building). To bridge the gap between qualitative methodology and CAQDAS, this article provides guidelines for researchers to familiarise themselves with widely used qualitative analysis strategies, and learn how ATLAS.ti, MAXQDA, and NVivo can be used in each phase of the qualitative analysis process. By effectively translating analytic strategies into CAQDAS features, CAQDAS can greatly facilitate data management, analysis, and collaboration when software features are harnessed to realise analytic strategies.


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