scholarly journals Thinking with Thinking with Theory in Qualitative Research

2015 ◽  
Author(s):  
Travis Marn
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Thematic Analysis ◽  
Social Life ◽  
Qualitative Data ◽  
First Generation ◽  
Alternative Account ◽  
Qualitative Data Analysis ◽  
Traditional Methods ◽  
Analyze Data

Thinking with Theory in Qualitative Research is a direct challenge to long held traditional forms of qualitative data analysis. Defining analysis methods like coding and thematic analysis to be reductive and simplistic, Jackson and Mazzei offer an alternative account of data analysis by “plugging-in” six poststructural theorists to data. Through interviews of two first generation academic women, Jackson and Mazzei demonstrate how researchers can employ complex theories to analyze data without relying upon traditional methods. The insightful, clear, and, at times, profound, findings of Thinking with Theory in Qualitative Research demonstrates the need for researchers to reexamine the continued reign of traditional forms of data analysis in the contexts of modern social life.

scholarly journals Data Analysis Methods for Qualitative Research: Managing the Challenges of Coding, Interrater Reliability, and Thematic Analysis

2018 ◽  
Author(s):  
Michael Belotto
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Thematic Analysis ◽  
Interrater Reliability ◽  
Qualitative Data ◽  
Sources Of Information ◽  
Qualitative Data Analysis ◽  
Qualitative Researcher ◽  
First Time ◽  
Data Analysis Methods

The purpose of this article is to provide an overview of some of the principles of data analysis used in qualitative research such as coding, interrater reliability, and thematic analysis. I focused on the challenges that I experienced as a first-time qualitative researcher during the course of my dissertation, in the hope that how I addressed those difficulties will better prepare other investigators planning endeavors into this area of research. One of the first challenges I encountered was the dearth of information regarding the details of qualitative data analysis. While my text books explained the general philosophies of the interpretive tradition and its theoretical groundings, I found few published studies where authors actually explained the details pertaining to exactly how they arrived at their findings. Some authors even confirmed my own experience that few published studies described processes such as coding and methods to evaluate interrater reliability. Herein, I share the sources of information that I did find and the methods that I used to address these challenges. I also discuss issues of trustworthiness and how matters of objectivity and reliability can be addressed within the naturalistic paradigm.

scholarly journals Analisis Data Kualitatif Dalam Penelitian Pariwisata

2018 ◽  
Author(s):  
Ilham junaid
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Literature Review ◽  
Thematic Analysis ◽  
Qualitative Data ◽  
Qualitative Data Analysis ◽  
Dominant Form ◽  
Tourism Research ◽  
Qualitative Research Methodology ◽  
Rich Data

This paper aims at exploring the definition, characteristics and stages of qualitative data analysis in tourism research. The paper is based on the writer’s experience in implementing qualitative data analysis as well as literature review on qualitative research methodology. Qualitative researchers may deal with different and rich data from qualitative methods. However, many qualitative researchers do not understand how to produce knowledge from qualitative data. For this reason, the result of a qualitative research tends to be descriptive without contributing to the advancement of knowledge. Thematic analysis is considered as a dominant form of analysis in qualitative research. Its stages consist of data reduction, organization and interpretation. Coding is the key for succeeding the qualitative data analysis. Hence, examples of qualitative data analysis in tourism research are provided to give practical stages of how to analyze qualitative data.

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.

scholarly journals Iterative Thematic Inquiry: A New Method for Analyzing Qualitative Data

2020 ◽  
Vol 19 ◽  
pp. 160940692095511
Author(s):  
David L. Morgan ◽  
Andreea Nica
Keyword(s):  
Qualitative Research ◽  
Content Analysis ◽  
Data Analysis ◽  
Thematic Analysis ◽  
Theoretical Basis ◽  
Qualitative Data ◽  
Qualitative Content Analysis ◽  
New Method ◽  
Data Collection And Analysis ◽  
Primary Procedure

Because themes play such a central role in the presentation of qualitative research results, we propose a new method, Iterative Thematic Inquiry (ITI), that is guided by the development of themes. We begin by describing how ITI uses pragmatism as a theoretical basis for linking beliefs, in the form of preconceptions, to actions, in the form of data collection and analysis. Next, we present the four basic phases that ITI relies on: assessing beliefs; building new beliefs through encounters with data; listing tentative themes; and, evaluating themes through coding. We also review several notable differences between ITI and existing methods for qualitative data analysis, such as thematic analysis, grounded theory, and qualitative content analysis. The use of ITI is then illustrated through its application in a study of exiters from fundamentalist religions. Overall, the two most notable features of ITI are that it begins the development of themes as early as possible, through an assessment of initial preconceptions, and that it relies on writing rather than coding, by using a continual revision of tentative results as the primary procedure for generating a final set of themes.

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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