The strength of the case study method is because it allows for the examination of the phenomenon in depth using various kinds of evidence obtained from interviews with those involved, direct observation of events and analysis of documents and artifacts Yin, Also, the case study was used because the focus of the study is more to describe and explain rather than prediction, and the variable variable studied is note easily unidentifiable or embedded in the phenomenon to be extracted for study Merriam, In addition, the case study allows for empirical inquiry of phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident Yin, Irrespective of which qualitative research design you adopted for your study, the three most common data collection techniques are the: You may have used one or more of these data collection techniques in your study.
Excerpt of the 'Data Collection Techniques' sub-section: Secondary data sources included documents provided by participants that pertain to the study Interviews were conducted based on questions listed in Interview Guide see Appendix C.
However, participants were allowed the freedom to talk about their experiences in a way in which they were comfortable In this sub-section, you give details about how you got your subjects or informants for your study. The issue of sampling can be quite confusing in qualitative research. Students often ask "how many subjects or informants" do I need for my study. Oftentimes, it is a difficult question to answer. Students should avoid applying the sampling principles of quantitative research.
The key consideration in sampling in qualitative research is "saturation" and not representativeness and the size of the sample is not statistically determined Neuman, The researcher worked in conjunction with the Head of Department, in choosing participants, based on their level of experience in caring for patients that suffer from dementia as well as their qualifications. There were 12 potential participants, of whom seven participated in the study. Some of the nurses were not available as they were off duty, off sick, on holiday, while others did not want to participate in the study In-person interviews were conducted and recorded in a quiet, neutral location where the participants were not in danger and there was no intimidation or coercion Chapter 3 Research Design and Methodology.
Some experts suggest that pilot-tests are not important for qualitative research while others suggest it would be useful for novice researchers to do pilot-test.
For example, if you are using interviews for the first time, it would advisable for you to conduct interview as a pre-exercise to get used to the type of data collection. The pilot test will assist the researcher in determining if there are flaws, limitations, or other weaknesses within the interview design and enable the researcher to make necessary revisions prior to the implementation of the study. However, the informants or participants involved in the pilot-test should similar to the informants involved in the final study.
It has also been suggested that the pilot test can the researcher with the refinement of research questions. A pilot-study was conducted with 3 senior managers and were interviewed at their workplace. The interview was audio-recorded to ensure correct use of the device.
During the exercise, attention was given to body language and non-verbal responses and the manner of asking questions. As the researcher was the main data collection instrument, the pilot-study provided an insight into phenomenon studied, increased experience in interviewing as well as enhanced interpersonal skills.
Also errors in interviewing skills were rectified and not repeated in the main study. You should include the following in this sub-section: Other sources include focus groups, observation without a predefined theory like statistical theory in mind for example , reflective field notes, texts, pictures, photographs and other images, interactions and practice captured on audio or video recordings, public e.
To analyse qualitative data, the researcher seeks meaning from all of the data that is available. The data may be categorized and sorted into patterns i. The ways of participating and observing can vary widely from setting to setting as exemplified by Helen Schwartzman's primer on Ethnography in Organizations In participant observation  researchers typically become members of a culture, group, or setting, and adopt roles to conform to that setting.
In doing so, the aim is for the researcher to gain a closer insight into the culture's practices, motivations, and emotions. It is argued that the researchers' ability to understand the experiences of the culture may be inhibited if they observe without participating. The data that is obtained is streamlined texts of thousands of pages in length to a definite theme or pattern, or representation of a theory or systemic issue or approach.
This step in a theoretical analysis or data analytic technique is further worked on e. An alternative research hypothesis is generated which finally provides the basis of the research statement for continuing work in the fields. Some distinctive qualitative methods are the use of focus groups and key informant interviews , the latter often identified through sophisticated and sometimes, elitist, snowballing techniques.
The focus group technique e. The research then must be "written up" into a report, book chapter, journal paper, thesis or dissertation, using descriptions, quotes from participants, charts and tables to demonstrate the trustworthiness of the study findings.
In qualitative research, the idea of recursivity is expressed in terms of the nature of its research procedures, which may be contrasted with experimental forms of research design. From the experimental perspective, its major stages of research data collection, data analysis, discussion of the data in context of the literature, and drawing conclusions should be each undertaken once or at most a small number of times in a research study.
In qualitative research however, all of the four stages above may be undertaken repeatedly until one or more specific stopping conditions are met, reflecting a nonstatic attitude to the planning and design of research activities. An example of this dynamicism might be when the qualitative researcher unexpectedly changes their research focus or design midway through a research study, based on their 1st interim data analysis, and then makes further unplanned changes again based on a 2nd interim data analysis; this would be a terrible thing to do from the perspective of an predefined experimental study of the same thing.
Qualitative researchers would argue that their recursivity in developing the relevant evidence and reasoning, enables the researcher to be more open to unexpected results, more open to the potential of building new constructs, and the possibility of integrating them with the explanations developed continuously throughout a study. Qualitative methods are often part of survey methodology, including telephone surveys and consumer satisfaction surveys.
In fields that study households, a much debated topic is whether interviews should be conducted individually or collectively e. One traditional and specialized form of qualitative research is called cognitive testing or pilot testing which is used in the development of quantitative survey items. Survey items are piloted on study participants to test the reliability and validity of the items.
This approach is similar to psychological testing using an intelligence test like the WAIS Wechsler Adult Intelligence Survey in which the interviewer records "qualitative" i. Qualitative research is often useful in a sociological lens. Although often ignored, qualitative research is of great value to sociological studies that can shed light on the intricacies in the functionality of society and human interaction.
There are several different research approaches, or research designs, that qualitative researchers use. As a form of qualitative inquiry, students of interpretive inquiry interpretivists often disagree with the idea of theory-free observation or knowledge. Whilst this crucial philosophical realization is also held by researchers in other fields, interpretivists are often the most aggressive in taking this philosophical realization to its logical conclusions.
For example, an interpretivist researcher might believe in the existence of an objective reality 'out there', but argue that the social and educational reality we act on the basis of never allows a single human subject to directly access the reality 'out there' in reality this is a view shared by constructivist philosophies. To researchers outside the qualitative research field, the most common analysis of qualitative data is often perceived to be observer impression.
That is, expert or bystander observers examine the data, interpret it via forming an impression and report their impression in a structured and sometimes quantitative form. In general, coding refers to the act of associating meaningful ideas with the data of interest. In the context of qualitative research, interpretative aspects of the coding process are often explicitly recognized, articulated, and celebrated; producing specific words or short phrases believed to be useful abstractions over the data.
As an act of sense making, most coding requires the qualitative analyst to read the data and demarcate segments within it, which may be done at multiple and different times throughout the data analysis process. In contrast with more quantitative forms of coding, mathematical ideas and forms are usually under-developed in a 'pure' qualitative data analysis.
When coding is complete, the analyst may prepare reports via a mix of: Some qualitative data that is highly structured e. Quantitative analysis based on codes from statistical theory is typically the capstone analytical step for this type of qualitative data. Contemporary qualitative data analyses are often supported by computer programs termed Computer Assisted Qualitative Data Analysis Software used with or without the detailed hand coding and labeling of the past decades.
These programs do not supplant the interpretive nature of coding, but rather are aimed at enhancing analysts' efficiency at applying, retrieving, and storing the codes generated from reading the data. Many programs enhance efficiency in editing and revision of codes, which allow for more effective work sharing, peer review, recursive examination of data, and analysis of large datasets.
A frequent criticism of quantitative coding approaches is against the transformation of qualitative data into predefined nomothetic data structures, underpinned by 'objective properties '; the variety, richness, and individual characteristics of the qualitative data is argued to be largely omitted from such data coding processes, rendering the original collection of qualitative data somewhat pointless.
To defend against the criticism of too much subjective variability in the categories and relationships identified from data, qualitative analysts respond by thoroughly articulating their definitions of codes and linking those codes soundly to the underlying data, thereby preserving some of the richness that might be absent from a mere list of codes, whilst satisfying the need for repeatable procedure held by experimentally oriented researchers.
As defined by Leshan ,  this is a method of qualitative data analysis where qualitative datasets are analyzed without coding. A common method here is recursive abstraction, where datasets are summarized; those summaries are therefore furthered into summary and so on. The end result is a more compact summary that would have been difficult to accurately discern without the preceding steps of distillation.
A frequent criticism of recursive abstraction is that the final conclusions are several times removed from the underlying data. While it is true that poor initial summaries will certainly yield an inaccurate final report, qualitative analysts can respond to this criticism. They do so, like those using coding method, by documenting the reasoning behind each summary step, citing examples from the data where statements were included and where statements were excluded from the intermediate summary.
Some data analysis techniques, often referred to as the tedious, hard work of research studies similar to field notes, rely on using computers to scan and reduce large sets of qualitative data. At their most basic level, numerical coding relies on counting words, phrases, or coincidences of tokens within the data; other similar techniques are the analyses of phrases and exchanges in conversational analyses.
Often referred to as content analysis , a basic structural building block to conceptual analysis, the technique utilizes mixed methodology to unpack both small and large corpuses. Content analysis is frequently used in sociology to explore relationships, such as the change in perceptions of race over time Morning , or the lifestyles of temporal contractors Evans, et al. Mechanical techniques are particularly well-suited for a few scenarios.
One such scenario is for datasets that are simply too large for a human to effectively analyze, or where analysis of them would be cost prohibitive relative to the value of information they contain. Another scenario is when the chief value of a dataset is the extent to which it contains "red flags" e.
Many researchers would consider these procedures on their data sets to be misuse of their data collection and purposes. A frequent criticism of mechanical techniques is the absence of a human interpreter; computer analysis is relatively new having arrived in the late s to the university sectors. And while masters of these methods are able to write sophisticated software to mimic some human decisions, the bulk of the "analysis" is still nonhuman.
Analysts respond by proving the value of their methods relative to either a hiring and training a human team to analyze the data or b by letting the data go untouched, leaving any actionable nuggets undiscovered; almost all coding schemes indicate probably studies for further research. Data sets and their analyses must also be written up, reviewed by other researchers, circulated for comments, and finalized for public review. Numerical coding must be available in the published articles, if the methodology and findings are to be compared across research studies in traditional literature review and recommendation formats.
Quantitative Research uses measurable data to formulate facts and uncover patterns in research. Quantitative data collection methods are much more structured than Qualitative data collection methods. Quantitative data collection methods include various forms of surveys — online surveys, paper surveys , mobile surveys and kiosk surveys, face-to-face interviews, telephone interviews, longitudinal studies, website interceptors, online polls, and systematic observations.
Snap has many robust features that will help your organization effectively gather and analyze quantitative data. While defining quantitative and qualitative research based on their uses and purposes may be considered a practical approach for researcher, the difference actually lies on their roots: Procedures, designs, concepts, purposes and uses emanate from there. Example on qualitative research referring to quality where problems are answered without generally focusing on quantity, are descriptions in words coming form interviews, discussions or observations.
However when words are translated to quantity in order to describe or to generalize, then the research is now called quantitatitive research. The bottom lines are the questions: Many thanks for giving me clear understanding around the differences between the qualitative and quantative research. Thanks a millions time. I was struggling to get an idea of how to approach the definitions. In fact I was even hesitating to answer the questions confidently.
Thanks for the distinct comparison between qualitative and quantitative Research, very very helpful. Thank you for making me to understand the difference between qualitative Research and quantitative research. Thanks a lot for the insightful distinction between Qualitative and Quantitative research.
Popular qualitative data collection methods used in business studies include interviews, focus groups, observation and action research. Moreover, grounded theory and document analysis can be also used as data collection method in qualitative studies.
A Guide to using Qualitative Research Methodology Contents 1. What is qualitative research? Aims, uses and ethical issues a) What is qualitative research? 2 b) When to use qualitative methods 3 c) Ethical issues 5 2. How to develop qualitative research designs a) The research question 7 b) The research protocol 8 c) A word on sampling 9 3.
Qualitative Research Methods Overview T his module introduces the fundamental elements of a qualitative approach to research, to help you understand and become proficient in the qualitative methods discussed in subse-. What’s the difference between qualitative and quantitative research? Susan E. DeFranzo September 16, Many times those that undertake a research project often find they are not aware of the differences between Qualitative Research and Quantitative Research methods.
Generally, 'methods' used in qualitative research are more flexible compared to the 'designs' or 'methods' used in quantitative research. Some argue that in qualitative research, the 'Research Design' sub-section is not essential. A popular method of qualitative research is the case study (Stake , Yin ), which examines in depth 'purposive samples' to better understand a phenomenon (e.g., support to families; Racino, ); the case study method exemplifies the qualitative researchers' preference for depth, detail, and context, often working with smaller and more focused samples, compared with the large samples of primary .