A comparative analysis of quantitative and qualitative research designs
In the conduct of sociological research, the qualitative and quantitative research designs remain the predominant structures in which scientific studies on social phenomena are discovered, analyzed, and interpreted. However, the emergence of quantitative research design prior to the development of the qualitative design created a dichotomy in the field of social science research, wherein preferences for each research design emerged. This dichotomy had been the central focus of discussions and debates about social science research: quantitative research is commonly associated with rigid scientific methodology and analysis, while qualitative research is considered more intrusive and less rigid in terms of data collection and analysis.
The dichotomy and differences between the qualitative and quantitative research designs led to the emergence of specific perceptions about each design. Quantitative research is considered more scientific than qualitative, while the latter is considered more in-depth in acquiring information than the former. While these perceptions are correct, each design has specific characteristics that make it unique and complementary to the other (design). This means that while they differ in methodology and analysis, quantitative and qualitative research designs actually present two facets of a social phenomenon or action. Thus, this paper posits how the quantitative and qualitative designs should be adopted based on the design's appropriateness to the problem of the study.
Delving into the components making up quantitative and qualitative researches, Smith (1988) categorizes each based on its units of analysis. Quantitative research is defined as the "counting and measuring of ... events, is often equated with scientific empiricism ... The approach is distinguished only by its use of numerical data as a means of understanding ...." Qualitative research, on the other hand, is considered as an approach that "rejects numerical measures in favor of narrative data ... data 'appear in words [sic] rather than in numbers ... (it) involves the critical analysis and synthesis of narrative information to derive verbal rather than statistical conclusions ... " (180).
Given these definitions and categorizations, it becomes evident that quantitative data was identified with numerical analysis, while qualitative is primarily concerned with textual analysis. Apart from this, the theoretical foundations of each design also differ. Quantitative designs, according to Babbie (1998), are primarily based on deductive theory construction, wherein statistical data are analyzed and interpreted from extant theories that are significantly related to a specific social phenomenon. Qualitative designs, meanwhile, are utilized for inductive theory construction, wherein a new theory would be generated from the data generated by the researcher (60-3). Data from qualitative research are based on observations, ethnography, and other techniques that bring into fore the salient features and dynamics of the social phenomenon.
Apart from the units of analysis and theoretical foundations of these designs, qualitative and quantitative researches also utilize different methodologies to generate information. Quantitative research designs are commonly applied through surveys and content analysis, while qualitative studies utilize in-depth interviews, participant observation or ethnography, and focus group discussions (FGDs) as its forms of data generation.
Extant literature on the qualitative-quantitative research designs dichotomy showed a gradual shift of social science studies from quantitative to qualitative. That is, as social science research developed through the years, the enumerated strengths of qualitative research increased, as more researches utilized this design in order to elicit substantial information about a social phenomenon that would otherwise have not been elicited through quantitative means.
Current issues pertaining to sociological research showed the prevalence and preference for the qualitative design. Bechhofer's (2004) analysis of the benefits of the qualitative research stemmed from his observation, as a researcher, that in the conduct of data generation and analysis through survey, "something has been lost" (46). Furthermore, apart from the loss of substantial meanings and interpretation of data in quantitative research, data "were made susceptible to machine analysis by post-coding," thereby reducing it (data) into a "relatively crude quantitative form" (49). His analysis proved that indeed, qualitative research is fast becoming a dominant research design, especially in the post-modernist period that characterizes society at present.
Devers and Robinson (2002) explicated in their journal article the essence of qualitative research to in uncovering meanings and expanding understanding of a social problem in question. For them, qualitative research "presuppose(s) the existence of multiple subjective realities that are continually being constructed and revised, the importance of interactional dynamics and the inherent worth and credibility of the participants ... They are particularly well-suited to explore phenomena that have not yet been fully described, that are social and interactional in nature ... " (242). This insight into the nature of qualitative research reflected how this type of design is best suited in analyzing social dynamics better than quantitative research does: qualitative research methods probe deeper into the dynamics and details of social communication and interaction than do quantitative research.
From these findings and analyses of qualitative research, more researchers and academicians now put premium on the flexibility of this design. Through interviews or FGDs, researchers are able to ask questions and generate information that has not been initially included in the questionnaire of interview schedule. Thus, follow-up questions and probing become possible, research benefits that are not found in quantitative researches.
However, qualitative research being a relatively new kind of research design in the field of social science, is also subjected to scrutiny in terms of its validity, reliability, and question of ethics. Qualitative research methods, despite their relative flexibility in generating data, is also under the threat of misjudgment, wherein researchers may become susceptible to disregarding informant anonymity and confidentiality of information, among others. Smythe (2001) discussed this particular point, asserting that "[r]esearchers then would be faced with the challenge of weighing the risks, benefits, and consent issues pertaining to any strategy used ... In all instances, researchers should comment in their manuscripts on the impact that their altering ... has on the scholarly value of their research report." In effect, full disclosure on the methodology, analysis, and interpretation conducted in qualitative research must be done to ensure that the data used are not only valid and reliable but also ethical (in terms of the procedures observed).
These benefits and issues pertaining to qualitative research illustrate its popularity and prevalent use in researches and studies in social science. However, it is important to note that there is also a contention that quantitative and qualitative researches should not be compared against each other, but be complemented with each other instead. As argued earlier in this paper, both designs actually complement in process of analyzing and interpreting data generated in order to explain social action, occurrences, or phenomena. Verschuren (2003) proposed that social science research must be based on two perspectives: the "tunnel vision" or the reductionist approach and the holistic observation approach.
The "tunnel vision" or reductionist approach is best suited for the quantitative research design, wherein the researcher generates "explanatory knowledge," by looking at the individual attributes and units related to the variables under study. The reductionist approach aims to generalize and describe the nature of each variable and interrelations among these variables (i.e., the variables' dynamics). The holistic observation approach is based on two important principles: (1) looking at an object as a whole and (2) the open-ended attitude of the researcher (131). Thus, while the reductionist approach looks only at the individual components making up the social action or phenomenon, the holistic observation pieces these variables together to create a holistic view of the social action or phenomenon under study. Verschuren stresses the importance of adopting these approaches in the conduct of social science research, for the researcher must be aware of the dynamics (interaction of variables with each other) as well as the nature (general description) of the social phenomenon.
Complementing qualitative with quantitative research is indeed a proposition that has…