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Comparison and Discussion on Best Practice Suggestions Report


Owing to the importance of research in enabling professional educators to think better, develop and understand educational principles, and make increasingly expansive and precise generalizations, there is a mounting need for educational researchers in every discipline to be knowledgeable on alternative research approaches if they are to make informed decisions about which approach to employ when embarking on a research study (Yilmaz, 2013).

Although many researchers continue to rely on qualitative and quantitative research approaches to undertake their studies, there is a third methodological tradition known as mixed methods research due to its propensity to cut across multiple methodologies and paradigms (Venkatesh, Brown, & Bala, 2013).

The report illuminates the similarities and differences of these research approaches and also discusses the best practice suggestions for the quantitative research approach.

Similarities and Differences of the Research Approaches

Qualitative research is defined as a type of research that explains phenomena according to numerical data which are analyzed by means of statistical methods and techniques, while qualitative research is defined as an emergent, inductive, interpretive and naturalistic approach to the study of individuals, cases, important phenomena, social situations and processes in their natural settings with the view to revealing in descriptive terms the meanings that individuals attach to their experiences of the world (Yilmaz, 2013).

On its part, “mixed methods research is an approach that combines quantitative and qualitative research methods in the same research inquiry” (Venkatesh et al., 2013, p. 21).

The documented similarities underlying the three research approaches include (1) presence of a problem or research question to which the researcher seeks answers (2) reliance on a plan of investigation to guide research, (3) reliance on data analysis strategies to provide meaning to the collected data, and (4) capacity of research findings to lead to change in the various attributes of interest (Venkatesh et al., 2013; Yilmaz, 2013).

In this report, the significant differences between the quantitative, qualitative, and mixed methods research approaches are discussed based on their ontological, epistemological, theoretical, and methodological underpinnings.

In ontological underpinnings (nature of reality), the quantitative research approach is objective as it portrays that social entities exist in reality external to social actors concerned with their existence, while qualitative research is subjective as it holds that social phenomena are created from the perceptions and consequent actions of the social actors concerned with their existence (Saunders, Lewis, & Thornhill, 2009).

While the quantitative approach views the social phenomena as having an objective reality that can be investigated in terms of generalizable causal effects and prediction, the qualitative approach not only considers reality as socially constructed but operates on the premise that the aim of scientific inquiry is to understand the phenomena of interest from the point of view of those being studied (Yilmaz, 2013).

In this sense, quantitative paradigms view reality as single and tangible, where the knower and the known are perceived as comparatively separate and independent; on the contrary, qualitative paradigms view reality as a multiple, socially and psychologically developed phenomenon, where the knower and the known are inexorably linked to each other (Gelo, Braakmann, & Benetka, 2008).

The ontological underpinnings of mixed methods research are in their initial stages of development.

In epistemological underpinnings (what constitutes acceptable knowledge in the field of study), it is essential to note that there are three distinctive epistemological orientations, namely positivism, realism, and interpretivism or constructivism (Yilmaz, 2013).

Both positivist and realist epistemological orientations are closely associated with the quantitative research tradition as they assume a scientific approach in the development of knowledge, with positivists perceiving the social science as an organized method for combining deductive logic with precise empirical observations of individual behavior, and realists believing that the social world exists as an objective truth independent of the human mind (Saunders et al., 2009).

In contrast, interpretivist or constructivist epistemological orientation is closely associated with the qualitative research approach as it claims that the social world is far too complex and multifaceted to lend itself to theorizing by definite “laws” in the same way as the physical sciences owing to the fact that the world is constructed, interpreted, and experienced by individuals in their interactions with each other and with broader social systems (Gelo et al., 2008).

On its part, the mixed methods approach is typified by “a practical/pragmatic attitude in that the research questions in empirical studies are given high priority, not philosophy of science, and in that qualitative and quantitative methods are used in combination for answering such questions” (Lund, 2012, pp. 155-156).

Drawing from this exploration, it is evident that all three research approaches are influenced by different epistemological orientations.

In theoretical underpinnings, it is quite clear that quantitative and qualitative approaches differ “in regard to the aims of scientific investigation as well as the underlying paradigms and meta-theoretical assumptions” (Gelo et al., 2008, p. 268).

These authors argue that, “while quantitative approaches are usually deductive and theory-driven (i.e., they observe specific phenomena on the bases of specific theories of reference), qualitative ones are inductive and data-driven (i.e., they start from the observation of phenomena in order to build up theories about those phenomena)” (p. 272).

Other differences arising from theoretical underpinnings employed by the two approaches include:

  1. quantitative research is more appropriate for hypothesis testing, while qualitative research is more appropriate for hypothesis generation,
  2. qualitative research obtains greater depth of the phenomena of interest to the study than quantitative research,
  3. quantitative research often results in better objectivity and generalizability of findings than qualitative research (Lund, 2012).

As demonstrated by this author, “the basic rationale of the mixed methods strategy is that by combining qualitative and quantitative methods one can utilize their respective strengths and escape their respective weaknesses” (p. 156).

In methodological underpinnings, it is quite clear that all the mentioned research approaches differ in terms of how data are collected and analyzed.

Available literature demonstrates that, while quantitative research requires the reduction of phenomena to numerical values to facilitate statistical analysis, qualitative research involves collection of data in a non-numerical form (e.g., texts, pictures, videos), and mixed methods research uses both numerical and non-numerical formats in collecting and analyzing data (Gelo et al., 2008).

In research designs, quantitative research employs experimental and non-experimental designs, while qualitative research employs naturalistic designs such as case study designs, discourse and conversation analysis designs, focus group designs, grounded theory designs, and ethnographic designs.

On its part, mixed methods research employs any of these designs or combines two or more designs depending on what they study intends to achieve (Gelo et al., 2008).

Best Practice Suggestions for Quantitative Research Approach

Owing to the objective nature of quantitative research and its epistemological underpinnings as discussed in this report, it is advisable that the researcher engages a large and representative sample with the view to ensuring that study findings can be generalized across populations, settings, and times.

It is also advisable that the researcher adopts rigorous sampling procedures in the development of a representative sample for use in quantitative research, with available literature demonstrating that the researcher can rely on probabilistic sampling (simple random sampling, systematic random sampling, stratified random sampling, cluster sampling), purposive sampling, as well as convenience sampling techniques to develop the required sample (Gelo et al., 2008).

To be able to get numerical data which can then be analyzed by means of statistical techniques to explain phenomena of interest, the best practice suggestions for collecting primary data in a quantitative research include tests or standardized questionnaires, structured interviews, and closed-ended observational protocols (Gelo et al., 2008).

Additionally, owing to the fact that the primary goals of quantitative research encompass prediction and hypothesis testing, it is always advisable that the researcher not only develops descriptive, comparative, and relationship-oriented research questions, but also uses a structured and predetermined research design (Echambadi, Campbell, & Agarwal, 2006).

The best practice suggestions for a quantitative research approach in data analysis include descriptive statistics and inferential statistics, while the best practice suggestions for data interpretation include generalization, prediction (theory-driven), as well as interpretation of theory.

Other best-practice suggestions for a quantitative research approach include

  1. using multiple items whenever possible to strengthen measurement,
  2. using stronger measures as instrumental variables,
  3. ensuring that the topics selected for investigation have obvious practical utility (Echambadi et al., 2006; Fassinger & Morrow, 2013).


This report has successfully illuminated the similarities and differences of quantitative, qualitative and mixed methods research approaches, not mentioning that it has discussed some of the best practice suggestions involving the quantitative research approach.

As already mentioned, the knowledge of these research traditions is critical for upcoming educational researchers in that it enables them to make informed decisions on which approach to utilize when conducting a research study.


Echambadi, R., Campbell, B., & Agarwal, R. (2006). Encouraging best practice in quantitative management research: An incomplete list of opportunities. Journal of Management Studies, 43(8), 1801-1820.

Fassinger, R., & Morrow, S.L. (2013). Toward best practices in quantitative, qualitative, and mixed methods research: A social justice perspective. Journal of Social Action in Counseling & Psychology, 5(2), 69-83.

Gelo, O., Braakmann, D., & Benetka, G. (2008). Quantitative and qualitative research: Beyond the debate. Integrative Psychological & Behavioral Science, 42(3), 266-296.

Lund, T. (2012). Combining qualitative and quantitative approaches: Some arguments for mixed methods research. Scandinavian Journal of Educational Research, 56(2), 155-165.

Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students, New York, NY: Pearson Education Limited.

Venkatesh, V., Brown, S.A., & Bala, H. (2013). Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems. MIS Quarterly, 37(1), 21-54.

Yilmaz, K. (2013). Comparison of quantitative and qualitative research traditions: Epistemological, theoretical, and methodological differences. European Journal of Education, 48(2), 311-325.

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1. IvyPanda. "Comparison and Discussion on Best Practice Suggestions." December 23, 2019. https://ivypanda.com/essays/comparison-and-discussion-on-best-practice-suggestions/.


IvyPanda. "Comparison and Discussion on Best Practice Suggestions." December 23, 2019. https://ivypanda.com/essays/comparison-and-discussion-on-best-practice-suggestions/.


IvyPanda. 2019. "Comparison and Discussion on Best Practice Suggestions." December 23, 2019. https://ivypanda.com/essays/comparison-and-discussion-on-best-practice-suggestions/.


IvyPanda. (2019) 'Comparison and Discussion on Best Practice Suggestions'. 23 December.

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