Stop making sense: the trials and tribulations of qualitative data analysis

Area ◽  
2008 ◽  
Vol 40 (2) ◽  
pp. 163-171 ◽  
Author(s):  
Pernille Schiellerup
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):  
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 2 (2) ◽  
pp. 210-220
Author(s):  
Wendelinus Oscar Janggo ◽  
Yuliana Wisnawati Nona Nungsi

This research is entitled “The Effectiveness of Using Cooperative Script Method to Improve Students’ Reading Comprehension on Recount Text of 8th Grade Students of SMP N Kewapante, Maumere in Academic Year 2017/ 2018”. The objective of this research is to investigate and to find out whether the use of cooperative script method effective to improve students’ reading comprehension on recount text. The method of this research is experimental research especially quasi experimental research. In analyzing the data, the researcher combined both quantitative and qualitative data analysis. In qualitative data analysis, the researcher used interview technique in order to get information about students’ perceptions in reading, while in quantitative data analysis, the researcher used SPSS version 16. The result of the research showed that the implementation of Cooperative Script Method in experimental class was more effective to help the students in reading comprehension on recount text compared to the use of the conventional method in control class of the eighth grade students of SMP N Kewapante, Maumere. It is also found that cooperative script method positively contributed to improve students’ reading comprehension. Therefore ,the researcher  suggests the teachers to use cooperative script method in order to improve students reading comprehension Additionally, cooperative script method can also motivate students to be more active, relax and enthusiastic to comprehend reading texts.


1993 ◽  
Vol 19 (3) ◽  
pp. 637-660 ◽  
Author(s):  
Richard A. Wolfe ◽  
Robert P. Gephart ◽  
Thomas E. Johnson

The development of software programs designed to facilitate qualitative data analysis has proltferated recently. Despite their potential to contribute much to management research, very little concerning the use of such programs has appeared in the management literature. The purpose of this paper is to review the current state of computer-facilitated qualitative data analysis [CQDA] in order to contribute to its effective use by management researchers. In an effort to achieve this purpose we discuss why CQDA programs are proliferating, describe the potential of such programs to contribute to management research, address program capabilities and features, describe CQDA applications in management research, and review issues researchers should be aware of in considering the use of C&DA.


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