A mixed method is an integrated strategy that defines each stage of the effect evaluation using methods and techniques from at least two or, more frequently, more social science fields. It incorporates quantitative and qualitative methods, and the team typically consists of experts in each evaluation discipline. Last but not least, the advantages of mixed methods come from combining both quantitative and qualitative methods, as one can use both to get a good picture of how different people and groups feel a change, what happened on the ground, and how practical the intervention effects were.
Mixed Methods: Definition and Use #
According to Creswell and Plano Clark (2011), mixed methods research refers to studies that have both quantitative and qualitative components. According to Tashakkori and Creswell, “mixed methods research is a research in which the investigator collects and analyses data, integrates the findings, and draws inferences using both qualitative and quantitative approaches or methods in a single study or programme of inquiry”  (pp.2).
Creswell and Plano Clark (2011) assert that this methodological pluralism approach provides greater insight than a single approach to specific research. They also set forward guidelines emphasizing crucial aspects of mixed-methods research. Additionally, Andrew & Halcomb (2006) emphasize that mixed methods research aims to exploit each method’s capabilities within a single study rather than to replace qualitative or quantitative research. To accomplish this, the researcher must select the best methodological approach for dealing with the current research question and provide a rationale for using the selected mixed methods design.
Mixed Methods Design Typology #
Mixed methods designs are categorized based on their category using a mixed methods typology. Although typology is useful, not every typology works well for every application. Following are six popular mixed methods designs that Creswell and Plano Clark (2011) proposed as typologies:
Sequential Explanatory #
The sequential explanatory design consists of two separate steps. Beginning with the collection and analysis of quantitative data, the design then moves on to the collection and analysis of qualitative data throughout a single research. The plan tries to interpret and comprehend quantitative study findings from a qualitative standpoint. The study’s interpretation phase prioritizes quantitative data and incorporates the findings.
Sequential Exploratory #
The first stage of the sequential exploratory design process is collecting and analysing qualitative data, followed by a quantitative data analysis stage. In-depth user interviews, focus groups, or an online survey with open-ended questions are frequently used as the first step in the design process. The qualitative data collection and analysis stage informs the ensuing quantitative investigation.
Sequential Transformative #
A theoretical perspective drives the two-phase sequential transformational design technique. This approach starts with gathering quantitative or qualitative data and then moves on to analyzing the results before incorporating them into the interpretation stage. Thus, in a sequential transformative design, interaction, prioritization, timing, and mixing of qualitative and quantitative strands are guided by a transformative conceptual framework of advocacy or empowerment, such as feminism or critical race theory.
Embedded Design #
With the embedded design, a single research study can include qualitative and quantitative data. While the other is used in a supporting or auxiliary role, one inquiry set is used as the main field of inquiry in the embedded design.
The researcher can incorporate data inside the inquiry thanks to the layered embedded architecture. As a result, the type of data that acts as the project’s guide is given priority, while the other type complements and is nested inside the core data collection. The layered technique gathers data at various levels or handles a subject other than the one now being discussed.
Triangulation Design #
As its name suggests, the triangulation design combines quantitative and qualitative data to triangulate and validate the research questions. It is achieved by collecting, analyzing, and interpreting different but complementary data on the same research question or study topic. The method’s strength lies in using the method’s strengths to overcome a weakness in one way. The triangulation strategy works best when the data quality is questionable; as a result, using additional methods and information from multiple sources helps to corroborate the findings and supports triangulation.
Multiphase Design #
As its name suggests, the multiphase design involves more than two phases, concurrent and sequential strands combined throughout the study, to achieve a general program goal.
Cresswell, J.W. (2009), Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (3rd ed.), Sage Publications Inc.
Greene, J.C., Caracelli, V.J. and Graham, W.F. (1989), “Toward a conceptual framework for mixed-method evaluation design”, Educational Evaluation and Policy Analysis, Vol. 11 No. 3, pp. 255-274.
Johnson, R.B. and Onwuegbuzie, A.J. (2004), “Mixed methods research: a research paradigm whose time has come”, Educational Researcher, Vol. 33 No. 7, pp. 14-26.
Tashakkori, A. and Teddlie, C. (Eds) (2003), Mixed Methods in Social and Behavioural Research, Sage Publications Inc.