scholarly journals Conducting Qualitative Data Analysis: Qualitative Data Analysis as a Metaphoric Process

2015 ◽  
Author(s):  
Ronald Chenail
Keyword(s):  
Data Analysis ◽  
Qualitative Analysis ◽  
Qualitative Data ◽  
Qualitative Data Analysis ◽  
Unit Of Analysis ◽  
Convincing Case

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.

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.

scholarly journals PENDAMPINGAN MENINGKATKAN MUTU MANAJEMEN PAUD BINAAN

2021 ◽  
Vol 6 (1) ◽  
pp. 36-43
Author(s):  
Yecha Febrieanitha Putri ◽  
Indah Dwi Sartika ◽  
Fahmi Fahmi
Keyword(s):  
Data Analysis ◽  
Quantitative Data ◽  
Qualitative Data ◽  
Action Plan ◽  
Participatory Action ◽  
Qualitative Data Analysis ◽  
Delivery Assistance ◽  
Quantitative Data Analysis ◽  
Using Data

The research aimed to find out whether the quality of PAUD management assistance could improve. Research-based service was carried out at RA Perwanida 3 and PAUD Kaisah. This study used the Participatory Action Research (PAR) model of the Kemmis, S. & McTaggart , R. Research methodology which was carried out in a series through online material delivery assistance and direct mentoring to each PAUD unit. The implementation of the activity is carried out in 5 steps, namely diagnosis, making an action plan, taking action, evaluating and reflecting. Data analysis using data analysis quantitative data analysis and qualitative data analysis. Quantitative data analysis was obtained from the description of the value of document completeness, pre and post mentoring. While the qualitative data analysis was obtained from field notes, documentation notes and interview notes using four parts, namely data reduction, display data and conclusion data. The results of the dedication research with assistance to improve the quality of the assisted PAUD management, the average document data obtained from each of the assisted institutions has increased by 37%, which is based on 30 assessment indicators, 26 indicators have been successfully fulfilled by each of the assisted PAUD institutions so that initially the average file completeness was 49% after being given assistance to 86%.

scholarly journals ANALYZING THE DEVELOPMENT OF TOURISM INDUSTRY IN SEVERAL CULTURAL EVENTS AT BATAM REGENCY, RIAU ISLAND PROVINCE

2016 ◽  
Vol 15 (2) ◽  
Author(s):  
Syailendra Reza Irwansyah Rezeki ◽  
Siska Amelia Maldin
Keyword(s):  
Data Analysis ◽  
Qualitative Data ◽  
Tourism Development ◽  
Tourism Industry ◽  
Qualitative Data Analysis ◽  
Cultural Events ◽  
Local Revenue ◽  
Cultural Event ◽  
Library Research

This study aimed to discover the development of tourism industry in several cultural events at Batam Regency, Riau Island Province. This is seen crucial as it deals with how the cultural event in tourism industry may affect the intensity of tourists’ revisit and tourism development. The data were obtained from interview and library research about the number of tourists’ visits on the cultural events and the increased number of the local revenue. The data were analyzed through qualitative data analysis. The results from the study showed how effective the cultural events to attract tourists’ revisit, develop the tourism industry, and local revenues. These are seen from the aspects like quality of accessibility, marketing, accommodation and venueKeywords: development, tourism industry, cultural event, tourists’ revisit, effectiveness

scholarly journals Communicating Qualitative Analytical Results Following Grice’s Conversational Maxims

2016 ◽  
Author(s):  
Jan Chenail ◽  
Ronald Chenail
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Data ◽  
Qualitative Data Analysis ◽  
Basic Assumptions ◽  
Analytical Results ◽  
Communicative Process ◽  
Scholarly Discussion

Conducting qualitative research can be seen as a developing communication act through which researchers engage in a variety of conversations. Articulating the results of qualitative data analysis results can be an especially challenging part of this scholarly discussion for qualitative researchers. To help guide investigators through this difficult communicative process, the authors suggest Grice’s (1989) Conversational Maxims of Quantity, Quality, Relation, and Manner as general guidelines to follow when formulating and presenting findings in qualitative research products as well as basic assumptions to guide readers when judging the quality of result representations.

scholarly journals The Study of Advertisement Quality of Message, Attractiveness, and Display Frequency Influence to Purchase Intention in Indonesia

2021 ◽  
Vol 4 (2) ◽  
pp. 466-479
Author(s):  
Dinar Annisa Susanti ◽  
Yulianita
Keyword(s):  
Data Analysis ◽  
Quantitative Analysis ◽  
Purchase Intention ◽  
Qualitative Data ◽  
Data Gathering ◽  
Qualitative Approach ◽  
Qualitative Data Analysis ◽  
Main Approach ◽  
Quota Sampling

The objective of this study was to find out the effectiveness of quality of message, attractiveness, and display frequency in Dove TV advertisement in influencing the purchase intention. This study was performed with quantitative as the main approach and supported by a qualitative approach to help explain the findings. The population of this study was the Indonesia TV. The sample was drawn using purposive and quota sampling. Therefore, there were 200 female respondents between 18 to 35 years old. Meanwhile, for qualitative data gathering, there were five resources. The resources are selected randomly from 200 respondents. After quantitative analysis of the data, it is revealed that all the variables in Dove TV advertisement have a positive and significant impact on purchase intention. It means the hypothesis 1, 2, and 3 were accepted. However, the strongest impact belongs to the quality of the message. Followed by display frequencies and the last is attractiveness. Despite that, there is only a slight difference between display frequencies and attractiveness. This result is also confirmed by qualitative data analysis. Hence, the marketers should pay more attention to the quality of the message rather than any variable, without neglecting others in creating the plan for advertisement.

Reinvigorating the human instrument

2020 ◽  
Vol 27 (2) ◽  
pp. 505-530
Author(s):  
Hendi Yogi Prabowo
Keyword(s):  
Data Analysis ◽  
Public Sector ◽  
Qualitative Analysis ◽  
Qualitative Data ◽  
Qualitative Evaluation ◽  
Behavioral Changes ◽  
Computer Assisted ◽  
Qualitative Data Analysis ◽  
Content Type ◽  
Corruption Prevention

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.

scholarly journals Communicating Qualitative Analytical Results Following Grice's Conversational Maxims

2014 ◽  
Author(s):  
Jan Chenail ◽  
Ronald Chenail
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Data ◽  
Qualitative Data Analysis ◽  
Basic Assumptions ◽  
Analytical Results ◽  
Communicative Process ◽  
Scholarly Discussion

Conducting qualitative research can be seen as a developing communication act through which researchers engage in a variety of conversations. Articulating the results of qualitative data analysis results can be an especially challenging part of this scholarly discussion for qualitative researchers. To help guide investigators through this difficult communicative process, the authors suggest Grice's (1989) Conversational Maxims of Quantity, Quality, Relation, and Manner as general guidelines to follow when formulating and presenting findings in qualitative research products as well as basic assumptions to guide readers when judging the quality of result representations.

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.

Making Sense of All the Words

2016 ◽  
pp. 197-211
Author(s):  
Janice E. Jones ◽  
A. J. Metz
Keyword(s):  
Data Analysis ◽  
Qualitative Analysis ◽  
Qualitative Data ◽  
First Impressions ◽  
Qualitative Data Analysis ◽  
Making Sense

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.

Bridging the Gap Between Methodology and Qualitative Data Analysis Software: A Practical Guide for Educators and Qualitative Researchers

2021 ◽  
pp. 136078042110035
Author(s):  
Neringa Kalpokas ◽  
Ivana Radivojevic
Keyword(s):  
Data Analysis ◽  
Qualitative Analysis ◽  
Qualitative Methodology ◽  
Qualitative Data ◽  
Model Building ◽  
Computer Assisted ◽  
Analysis Software ◽  
Qualitative Data Analysis ◽  
Qualitative Data Analysis Software ◽  
Data Analysis Software

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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