scholarly journals Introduction to Special Issue: Diverse Approaches to Qualitative Data Analysis for Applied Research

2021 ◽  
Author(s):  
Jessica Lester ◽  
Noah Goodman ◽  
Michelle O'Reilly
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Analysis ◽  
Qualitative Data ◽  
Applied Research ◽  
Special Issue ◽  
Qualitative Data Analysis ◽  
Data Set ◽  
Shared Data ◽  
Qualitative Approaches

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.

scholarly journals Playing Set® to Discover Qualitative Data Analysis

2015 ◽  
Author(s):  
Jean Scandlyn ◽  
Sarah Hautzinger
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Data ◽  
Team Building ◽  
Card Game ◽  
Qualitative Data Analysis ◽  
Multiple Components ◽  
Qualitative Approaches ◽  
Qualitative Evidence ◽  
Health Related

This article describes the use of an experiential classroom exercise using the card game Set® to introduce concepts related to qualitative approaches to research design and analysis, particularly those based in an interpretive framework. The multiple components of the game, which centers on visual pattern recognition, parallel the “organic” complexity of ethnographic investigation and demonstrate how strong interpretations can be supported with qualitative evidence. The first author adapted the exercise, originally developed by the second author for teaching undergraduate anthropology students, for use in workshops teaching qualitative research to mid - career professionals working on health - related projects in Bolivia. In the process the first author discovered that the game was also useful in team - building in a workshop setting, providing a base of shared experience to which participants could refer as they grappled with the intellectual and emotional issues that arose while designing their own research projects and discovering the system and rigor of qualitative data analysis. An unanticipated finding was the exercise’s usefulness in demonstrating the distinction between and complementarity of inductive and deductive approaches in qualitative research.

scholarly journals Exploratory Geovisualizations for Supporting the Qualitative Analysis and Synthesis of Place-Related Emotion Data

2019 ◽  
Author(s):  
Susanne Bleisch ◽  
Daria Hollenstein
Keyword(s):  
Data Analysis ◽  
Qualitative Analysis ◽  
Data Model ◽  
Qualitative Data ◽  
Elderly Women ◽  
Qualitative Data Analysis ◽  
Data Set ◽  
Personal Significance ◽  
Generic Data ◽  
Generic Data Model

Locations become places through personal significance and experience. While place data are not emotion data, per se, personal significance and experience are often emotional. In this paper, we explore the potential of using visual data exploration to support the qualitative analysis of place-related emotion data. To do so, we draw upon Creswell’s (2009) definition of place to define a generic data model that contains emotion data for a given location and its locale. For each data dimension in our model, we present symbolization options that can be combined to create a range of interactive visualizations, specifically supporting re-expression. We discuss the usefulness of example visualizations, created based on a data set from a pilot study on how elderly women experience their neighborhood. We find that the visualizations support four broad qualitative data analysis tasks: revising categorizations, making connections and relationships, aggregating for synthesis, and corroborating evidence by combining sense of place with locale information to support a holistic interpretation of place data. In conclusion, the paper contributes to the literature in three ways. It provides a generic data model and associated symbolization options, and uses examples to show how place-related emotion data can be visualized. Further, the example visualizations make explicit how re-expression, the combination of emotion data with locale information, and visualization of vagueness and linked data support the analysis of emotion data. Finally, we advocate for visualization-supported qualitative data analysis in interdisciplinary teams so that more suitable maps are used and so that cartographers can better understand and support qualitative data analysis.

scholarly journals ANALYSIS OF SLANG WORDS FORMATION FOUND IN THE LYRICS OF DRAKE’S SONGS

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
I.P.A. Bhuwana ◽  
I.G. Budasi ◽  
G. Mahendrayana
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Data ◽  
Document Analysis ◽  
Word Formation ◽  
Formation Processes ◽  
Qualitative Data Analysis ◽  
Music Film ◽  
Descriptive Qualitative

The development of music, film, and other industry of entertainment is stated to contribute to the existence of slang words. There are so many slang words that become popular after they are included in the lyrics of songs. One of them is YOLO (You Only Live Once) which is popularized by Drake. In relation to that, this descriptive qualitative research attempts to find out the types and word formation processes of slang words found in the lyrics of Drake’s songs. By taking the model of document analysis by Bowen (2009) and Qualitative data analysis by Miles and Hubberman (1994), it is found out that there are 190 slang words existing in the lyrics of Drake’s songs. They are respectively categorized into Clipping type (62 slangs), Fresh and Creative type (44 slangs), Compounding type (44 slangs), Imitative type (36 slangs), and Acronym type (4 slangs).

scholarly journals A Call for Enhancing Saturation at the Qualitative Data Analysis Stage via the Use of Multiple Qualitative Data Analysis Approaches

2019 ◽  
Author(s):  
Amber Sechelski ◽  
Anthony Onwuegbuzie
Keyword(s):  
Qualitative Research ◽  
Discourse Analysis ◽  
Data Analysis ◽  
Qualitative Data ◽  
Research Process ◽  
Comparison Analysis ◽  
Qualitative Data Analysis ◽  
Data Analyses ◽  
Multiple Data

The analysis of data represents the most important and difficult step in the qualitative research process. Thus, recently, a few authors have written methodological works that contain discussion of an array of qualitative data analysis approaches. Yet, despite the call of Leech and Onwuegbuzie (2007) a decade ago for qualitative researchers to analyze a given set of qualitative data in multiple ways, this practice has been largely ignored. Thus, in this article, we bolster the argument for conducting multiple data analyses. In particular, we use data stemming from an interview to demonstrate how using five qualitative data analysis approaches (e.g., constant comparison analysis, discourse analysis) helped to enhance what we refer to as analysis saturation, thereby increasing verstehen (i.e., understanding).

Embracing tension: using Bakhtinian theory as a means for data analysis

2016 ◽  
Vol 17 (1) ◽  
pp. 20-36 ◽  
Author(s):  
Xiaoli Hong ◽  
Michelle M Falter ◽  
Bob Fecho
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Data ◽  
Multiple Perspectives ◽  
Qualitative Data Analysis ◽  
Research Participants ◽  
Analysis Process ◽  
Bakhtinian Theory ◽  
Ongoing Dialogue

In this article we introduce tension as a means for qualitative data analysis based on Mikhail Bakhtin’s dialogical theory. We first explain the foundations of Bakhtin’s theory and show the inevitability of tension in our lives and qualitative data analysis. We then offer a review of how Bakhtin’s notion of tension has manifested itself in qualitative research, which prompts us to establish a tensional approach to qualitative data analysis. Finally, we outline our framework for a tensional approach to data analysis and illustrate examples of putting this approach into practice in our own study. Our tensional approach (1) explores key moments of tension; (2) seeks out unease and discomfort; (3) involves researcher and research participants in ongoing dialogue; (4) and embraces multiple perspectives on a range of tensions during the data analysis process. It encourages uncertainties and questions instead of pursuing certainty of meaning and fixed conclusions.

Jack + Jill, and Joey in paradise: CAQDAS Conference 07

KWALON ◽  
2007 ◽  
Vol 12 (2) ◽  
Author(s):  
Hennie Boeije ◽  
Jeanine Evers
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Data ◽  
Computer Assisted ◽  
Qualitative Data Analysis

Op Royal Holloway College, universiteit van Londen, werd dit jaar de tweede conferentie over CAQDAS – computer-assisted qualitative data-analysis – gehouden. Het was er van de 17e tot de 19e april zonnig en gezellig. Organisator was het CAQDAS Networking Project van de universiteit van Surrey. De wortels van dat project, dat nu officieel dertien jaar bestaat, liggen in 1989 bij de conferentie Using Computers in Qualitative Research. Dit jaar ging het over Advances in Qualitative Computing.

Introduction to Qualitative Data Analysis

2021 ◽  
pp. 140-172
Keyword(s):  
Qualitative Research ◽  
Grounded Theory ◽  
Data Analysis ◽  
Qualitative Data ◽  
Qualitative Data Analysis ◽  
The Third ◽  
Constant Comparative ◽  
Analytic Induction

This chapter introduces readers to the basics of data analysis and the practical handling of open, axial, and selective coding within and outside the grounded theory. Readers are introduced to segmentation/reassembling, constant comparative, and analytic induction concepts in qualitative data analysis in the first section of this chapter. They should be able to trace the origin of coding of qualitative data in qualitative research. The stages of qualitative data analysis are discussed in the second section. The third section takes readers through the practical steps of open, axial, and selective coding, and detailed examples are given.

Teaching Qualitative Data Analysis Through Gaming

2018 ◽  
Vol 25 (9-10) ◽  
pp. 1085-1090 ◽  
Author(s):  
Leo A. Mallette ◽  
Johnny Saldaña
Keyword(s):  
Data Analysis ◽  
Qualitative Analysis ◽  
Qualitative Data ◽  
Narrative Construction ◽  
Qualitative Data Analysis ◽  
Basic Principles

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.

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.

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