Approaches (on this site) refer to an integrated package of options (methods or processes). For example, 'Randomized Controlled Trials' (RCTs) use a combination of the options random sampling, control group and standardised indicators and measures.
A strengths-based approach designed to support ongoing learning and adaptation by identifying and investigating outlier examples of good practice and ways of increasing their frequency.
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An approach that focuses on assessing the value of an intervention as perceived by the (intended) beneficiaries, thereby aiming to give voice to their priorities and concerns.
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A research design that focuses on understanding a unit (person, site or project) in its context, which can use a combination of qualitative and quantitative data.
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An approach designed to support ongoing learning and adaptation, which identifies the processes required to achieve desired results, and then observes whether those processes take place, and how.
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An impact evaluation approach based on contribution analysis, with the addition of processes for expert review and community review of evidence and conclusions.
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An impact evaluation approach that iteratively maps available evidence against a theory of change, then identifies and addresses challenges to causal inference.
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An approach used to surface, elaborate, and critically consider the options and implications of boundary judgments, that is, the ways in which people/groups decide what is relevant to what is being evaluated.
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Various ways of doing evaluation in ways that support democratic decision making, accountability and/or capacity.
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An approach designed to support ongoing learning and adaptation, through iterative, embedded evaluation.
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A stakeholder involvement approach designed to provide groups with the tools and knowledge they need to monitor and evaluate their own performance and accomplish their goals.
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A particular type of case study used to jointly develop an agreed narrative of how an innovation was developed, including key contributors and processes, to inform future innovation efforts.
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A way to jointly develop an agreed narrative of how an innovation was developed, including key contributors and processes, to inform future innovation efforts.
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A particular type of case study used to create a narrative of how institutional arrangements have evolved over time and have created and contributed to more effective ways to achieve project or program goals.
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Approach primarily intended to clarify differences in values among stakeholders by collecting and collectively analysing personal accounts of change.
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An impact evaluation approach suitable for retrospectively identifying emergent impacts by collecting evidence of what has changed and, then, working backwards, determining whether and how an intervention has contributed to these changes.
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An impact evaluation approach which unpacks an initiative’s theory of change, provides a framework to collect data on immediate, basic changes that lead to longer, more transformative change, and allows for the plausible assessment of the initiative’s contribution to results via ‘boundary partners’.
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A range of approaches that engage stakeholders (especially intended beneficiaries) in conducting the evaluation and/or making decisions about the evaluation.
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A participatory approach which enables farmers to analyse their own situation and develop a common perspective on natural resource management and agriculture at village level.
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A strengths-based approach to learning and improvement that involves intended evaluation users in identifying ‘outliers’ – those with exceptionally good outcomes - and understanding how they have achieved these.
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An impact evaluation approach without a control group that uses narrative causal statements elicited directly from intended project beneficiaries.
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An impact evaluation approach that compares results between a randomly assigned control group and experimental group or groups to produce an estimate of the mean net impact of an intervention.
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A Rapid Evaluation is an approach that uses multiple evaluation methods and techniques to quickly and systematically collect data when time or resources are limited.
Many terms are used to describe these approaches, including real time evaluations, rapid feedback evaluation, rapid evaluation methods, rapid-cycle evaluation and rapid appraisal. The common feature of these different models is the expedited implementation timeframes which generally range from 10 days to 6 months.
An approach especially to impact evaluation which examines what works for whom in what circumstances through what causal mechanisms, including changes in the reasoning and resources of participants.
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An participatory approach to value-for-money evaluation that identifies a broad range of social outcomes, not only the direct outcomes for the intended beneficiaries of an intervention.
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An approach to decision-making in evaluation that involves identifying the primary intended users and uses of an evaluation and then making all decisions in terms of the evaluation design and plan with reference to these.
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Mixed methods research is a research method that combines and integrates qualitative and quantitative research methods in a single research study. It involves collecting and analyzing qualitative and quantitative data to understand a phenomenon better and answer the research questions.
The central premise of using mixed methods research is that it makes the most of the strengths of each data type while neutralizing their weaknesses. Researchers combine qualitative and quantitative methods to expand their evidence, improve the credibility of their findings, and illustrate the results from one method with the results from the other one.
The three core mixed methods research designs are convergent design, explanatory sequential design, and exploratory sequential design. Let’s take a look at these three types of mixed methods research designs:
1. Convergent design
Convergent design is a type of mixed methods research in which you collect quantitative and qualitative data simultaneously and analyze them separately. After the analysis, you then combine or compare the results to draw a conclusion. Convergent design is used when there is a need to compare statistical results with qualitative findings to understand the research problem better. Researchers also use this mixed qualitative and quantitative research methods design to validate and illustrate qualitative findings with quantitative results.
2. Explanatory sequential design
Explanatory sequential design is a type of mixed methods research in which you first collect and analyze quantitative data and then follow the results up with a qualitative phase. In this approach, researchers implement the qualitative phase to explain initial quantitative results in more depth.
3. Exploratory sequential design
Exploratory sequential design is a type of mixed methods research design in which you collect and analyze qualitative data and then follow up your results with a quantitative phase. This mixed qualitative and quantitative research methods design aims to explore a phenomenon before deciding which variables you need to measure quantitatively.
There is no clear-cut procedure for conducting a study using mixed methods. However, you can conduct mixed methods research by following the steps below:
Determine whether mixed methods research is appropriate
The first step is to determine whether mixed methods research is appropriate for answering your questions and offer the best kind of evidence you need for your research study.
Determine your purpose
Determine the purpose you want to achieve by using mixed methods research design. Is it to use the results from one data type to corroborate, expand, develop, or complement the other?
Select the most appropriate design
Select the most appropriate design out of the three types of mixed methods research designs.
Convergent design is suitable when you need both qualitative and quantitative data, have limited time to collect the data, and must gather the required data in one visit.
Explanatory design is appropriate if the research problem is quantitatively oriented and the variables and instruments required for the research are available.
Exploratory design is best when the variables are unknown and the instruments needed are not available. This is also the best mixed methods research approach to use if there is no guiding theory for the study.
Collect qualitative and quantitative data.
Collect the qualitative and quantitative data you’ll analyze. Check our our guide to qualitative methods to learn about different ways to collect qualitative data.
Analyze the collected data.
Analyze the collected data. You can use the Delve qualitative data analysis tool to quickly and rigorously analyze your qualitative data. You can then export the data into spreadsheets to analyzed it along with your quantitative data.
Write the research report
Validate and interpret the data and write your research report.
Here is a real world mixed methods research example to help you better understand this research approach.
In Newman, Shell, Ming, Jianping, and Mass’ paper on adolescent alcohol use, the researchers used the mixed methods research approach to understand the characteristics of adolescents who drink and don’t drink alcohol. The researchers utilized exploratory sequential design. They started by collecting and analyzing qualitative data sourced through in-depth interviews, discussions, and observations to develop a clear view of the behaviour from the participants’ perspective.
Then the researchers used the qualitative findings to design survey instruments used to collect quantitative data to explore the behavior in more detail and with a bigger sample. Using mixed methods research, the researchers gained a better understanding of this health-related behaviour and provided insights on how to reduce alcohol-related risks among young adults.
The main benefit of using mixed methods research is that you get the best of both qualitative and quantitative research methods. This approach allows you to use the strength of one data type to mitigate the weakness of the other.
Mixed qualitative and quantitative research methods are less tied to established research paradigms, so they are flexible to use.
Mixed methods research allows you to tackle a broad range of research questions. This is because you are not limited to a research method.
This approach helps researchers get stronger evidence to collaborate their findings.
Mixed methods research gives researchers a complete understanding of the topic or phenomenon under study.
Mixed methods research requires collecting and analyzing two types of data, so it is labor-intensive and time-consuming.
Results from mixed methods research can be difficult to interpret if you get different results from the two data types.
Mixed methods research requires you to understand multiple methods and how to combine them appropriately.