Comparing Qualitative And Quantitative Approaches Case Studies Example
How might a qualitative study investigate the experience of depression compared to a quantitative study such as a survey?
Research Question (How would the approaches differ in what is asked?)
This question basically asks how the two approaches to research differ when it comes to the research question that they are trying to address. In general, there are research questions that may be intended to be addressed by means of a qualitative research and the same actually goes for quantitative research. One good way to know whether a research question can be appropriately addressed by either a qualitative or quantitative research is to know the main objective of each. Qualitative researchers aim to answer a research question by describing any specific phenomena in a deeper and comprehensive manner (as in the case of phenomenological research) .
There are sources that suggest that qualitative research is often used as a prelude to quantitative research. In the same manner, there are also some that suggest that despite the said practice (i.e. use of qualitative research as a prelude to deeper quantitative studies with a larger number of participants), it may be the other way around—that is, quantitative research is done first before qualitative—provided that we are talking about the same scope of research or even directly related research objectives. When it comes to the research questions that are asked, qualitative research questions are often open ended or those that cannot be answered by yes or now. This is because one of the main objectives of the qualitative approach is not just to know or discover facts but to understand a phenomena or in more specific cases, human behavior or describe the relationship between a set of two or more variables . Quantitative research questions, on the other hand, are often questions that are closed ended; those whose answers are fixed and measurable. This is because the rationale of most researchers who use this approach is to know and discover the facts about certain phenomena—nothing more and nothing less, and not really to understand it deeply as in the case of qualitative research.
As an example of a qualitative question for this scenario, we can conduct a research asking “The Effects of Excessive Exposure to Online Games on Depression Rates among Adolescents”.
Sample Recruitment (How would the approaches differ in selecting people to study?)
There are numerous types of sampling or recruitment techniques. Some of the commonly used sampling techniques in the field of research are convenience sampling, random sampling, stratified random sampling, snowball sampling, and systematic sampling. The same principle used in selecting which among a qualitative or a quantitative research approach is to be implemented, in fact, applies when it comes to the determination of the appropriate sample recruitment technique to be used. That is, the researchers should know which sampling procedures are best used for qualitative researchers and which for quantitative researches.
When it comes to conducting a qualitative research, for example, one established principle is that the sample size does not matter—that is, recruiting either a large or small number of samples or participants, in general, does not affect the reliability of the results which is in contrast with the importance of sample size in a quantitative research.
This striking difference between the two when it comes to sample recruitment may be caused by the difference between the assumptions used in the two approaches. Whenever a researcher uses a qualitative approach, for example, he somewhat assumes that the samples or the relationship between the samples and the variables in the conceptual or research framework that he created would be not predictable (hence they cannot be described by fixed means such as numbers and statistics); while a researcher using the quantitative approach, on the other hand, believes that the samples and the relationship between the samples and variables in the research framework, are fixed and can therefore be predictable.
Purposive sampling is a type of sampling where the selection of samples is based mainly on the judgment of the researcher. Probability sampling, on the other hand, is where there is an element of randomization or random selection of participants. There are some types of probability sampling that uses a certain process in order to assure that every population has equal probabilities of being selected as a participant. In this case, considering that the research problem that was posed is qualitative in nature, the more appropriate sampling procedure would be the purposive sampling.
Data Collection (How would approaches differ in what is asked of the data?)
Qualitative and quantitative researches greatly differ when it comes to the appropriate approaches used in data gathering or collection. In a qualitative research, for example, researchers often gather information from the participants by using one on one interview, group interviews, focus group discussions, essays, and perhaps the easiest form of data gathering in qualitative research, participant observation. Within the context of quantitative research, on the other hand, data gathering procedures such as surveys using functional outcome tools are often used. Quantitative researchers are often free to use whatever type of outcome measuring tool they want as long as it is measurable—because this is the quality that would make their research a quantitative one.
Also, in a qualitative research, all sorts of information can be asked or obtained from the participants. Most, questions, however, are open ended questions—meaning, questions that are not answerable by yes or no or any fixed or measurable things . Quantitative research on the other hand uses questions that are fixed and measurable by numbers and other quantifiers.
In the research question that was posed, the most appropriate and efficient data collection technique would be the one on one interview with the respondents. This way, the researchers can better explore the participation of any variables and gather information relevant to the research question from the respondents. Questions that can be asked to the respondents may be ones like: “how do you think having a lot of online game playing time has affected your life in general”, and “do you think playing a lot of online games has affected you or your life in any way positive or negative, if not both” can both be good starts. The important thing is not to be leading when asking qualitative questions.
Data Analysis (How would the approaches differ in what is asked of the data?)
The main goal of the data analysis part of a qualitative research is to provide a basis for a complete and detailed description of the phenomenon being investigated or the research question. In analyzing qualitative data, researches often rely on logic (e.g. reconstructed logic) and reasoning skills (e.g. inductive reason as in the concept of grounded theory) to find the correlation between variables, if any. The weakness of this data analysis approach, however, is that it does not provide a high level of reproducibility unlike statistically reliable data analysis methods.
The main goal of the same part in a quantitative research, on the other hand, is to be able to provide a basis that is statistically reliable (i.e. reproducible), and generalizable (this is where the size of the sample population matters wherein a larger size equals a higher level of generalizability and then vice versa). The weakness of this approach, however, is that it only offers a one-dimension or a fixed answer to the research question.
Considering the research question posed earlier, the appropriate data analysis method would be by means of simply interpreting and then summarizing the responses of the subjects during the one on one interview sessions conducted. The important thing to remember here is that everything starting from the research question should be selected carefully based on whether the research question can be answered by either a qualitative or a quantitative approach.
Inferences and Generalizations you can draw from the data (How would the approaches differ in the kind of findings that are produced from the analysis)
It is important for authors of academic researches and studies to be specific when it comes to the research design and methods that they will use, just like how they are required to be specific when it comes to the research question that they are going to address. In general, there are two ways how to conduct a research: first, via qualitative research and second, via quantitative research. When it comes to the inferences and generalizations that can be drawn from the gathered data, the clearest and most precise answer would be it depends. The generalizations and inferences would depend on the type of research question, the research design and method used the data analysis tools and strategies used, etc.
There are literatures about research that suggest that the research statement or question is an important variable to consider in differentiating the conclusions that can be drawn from the research. This is mainly because the answer that the researchers are expecting to find or are trying to find is already openly revealed in the research question. In general, however, qualitative researches’ inferences and generalizations offer a more specific, albeit variable view on the answer to a research question whereas that of quantitative researches offer a more narrowed down or measurable set generalizations and inferences.
Validity and reliability are two aspects of research that can be used to determine its quality. That is, a highly valid and reliable research can be perceived as a high quality research. Most qualitative researches struggle in these two areas because the data analysis part is often conducted using the author’s judgment and knowledge about the topic, which automatically shows that there is a certain degree of bias in the analysis and therefore the conclusions that would be drawn later on. In comparison, quantitative researches are the ones who excel in these two aspects because unlike qualitative researches, they are free from biases and are highly objective.
Grounded Theory in Qualitative Research
There are numerous ways how to collect data that will be used for qualitative research. In the same manner, there are also numerous ways how to analyze them and more often than not, academicians perceive that no matter how careful the authors of qualitative researchers tell they have been when analyzing the data they gathered, the factor that is the researchers’ personal bias and prejudice regarding the topic that they are researching can never be completely removed .
This is where the purpose of inductive approach in analyzing qualitative data comes in. Grounded theory is one of the types of qualitative data analytic strategies used by researches. According to Thomas (2006), one of the main reasons why grounded theory is preferred by most researchers of qualitative studies “consistent with the general patterns of qualitative data analysis” as described by previous authors who researched on the topic; and that it excels in data reduction, data display, and conclusion drawing or verification, as opposed to non-inductive and other inductive approaches in analyzing qualitative data.
Additionally, in some qualitative researches that deals with more complex data, population, or variable, certain theories may be developed—via the inductive approach (an example of which is grounded theory), which the researchers may then use to have a more concrete and verifiable explanation about the phenomenon or research problem that they are studying .
One method used in grounded theory is the constant comparative method. Researchers who use this grounded theory method often are those who try to identify a phenomenon, focal concepts and principles, among others. Theoretical sampling, on the other hand, pertains to the process of generating theory that starts from the collection of data from a large pool of sources followed by making decisions what data to collect next and where to find them, developing a new theory along the process .
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