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June 17, 2021Primary and secondary dataAll data are categorized as either ‘primary data’ or ‘secondary data,’ based on how you source them. Primary data are those that you and your team collect directly from the main sources, whereas, secondary data are those that were collected by other organisations, government agencies, or independent research institutions and individuals and are available for use. Secondary data could be censuses, surveys, organizational records or other previous research, extracted from books, journals, reports, newspapers, magazines, data archives, databases etc. Once you are ready to collect your data, you will have to decide upon the data collection tools and methods. This will depend on a number of things, including the purpose of the data, the local context, cost, timeline, availability of skills and resources, and most importantly, the indicators and key questions you have identified and how the collected data will be utilized. All data are further divided into two broad categories based on the techniques employed in the field to gather and analyse them – ‘qualitative data’ and ‘quantitative data.’ Stay with us as we walk you through each approach and explain their key differences. Qualitative data collection approachQualitative data collection plays an important role in monitoring and evaluation as it helps you delve deeper into a particular problem and gain a human perspective on it. It provides in depth information on some of the more intangible factors like experiences, opinions, motivations, behaviours or descriptions of a process, event or a particular context relevant to your project. So, in other words, a qualitative approach uses people’s stories, experiences and feelings to measure change. Compared to a quantitative approach, a qualitative approach is more open, informal and unstructured or semi-structured, and it provides more flexibility in how data is collected. Qualitative research is investigative in nature and the data collected through this process answers the question ‘why’ or ‘how’ – how do people feel about a situation, or why are health care facilities underutilized? This approach relies more heavily on interactive interviews, discussions and deeper conversations. While using this approach, many researchers also use triangulation or mixed methods to increase the credibility and authenticity of their findings. Data is often recorded in the form of field notes, sketches, audiotapes, photographs and other suitable means. Usually the findings drawn from qualitative research are not generalizable to any specific population, rather each case study produces a unique piece of evidence that can help identify patterns among different studies of the same issue. The results produced from this approach can be subjective and as such can be subject to bias in their interpretation. Analyzing such data can also be quite complex and time-consuming which can make it an expensive process. Quantitative data collection approachThe quantitative approach uses numbers and statistics to quantify change and is often expressed in the form of digits, units, ratios, percentages, proportions, etc. Compared to the qualitative approach, the quantitative approach is more structured, straightforward and formal. Quantitative approach is utilized to derive answers to the questions ‘how much’ or ‘how many’ – how many people attended the workshop or how often do people visit the health center. Quantitative research is useful for multi-site and cluster evaluations that involve a large group of respondents or sample population. This approach relies heavily on random sampling and structured data collection instruments that fit diverse experiences into predetermined response categories. Typical quantitative data gathering strategies include, experiments or clinical trials, gathering relevant data from management information systems, administering surveys with closed-ended questions or observing and recording well-defined events. Because quantitative methods are not about gaining an in-depth understanding but rather grasping a general understanding of a particular context with precise results, quantitative data is easier to collect and analyse and there are less chances of bias in the result interpretation. Results are numerical, objective, conclusive and to the point, so the results are easier to summarize and generalize and are useful for making comparisons across different sites or interventions. Differences between qualitative and quantitative data collection approachQualitative and quantitative data collection methodsBelow, we have summarized key data collection methods and tools used in monitoring and evaluation (M&E). Most methods and tools can be used in combination with other tools and methods and are applicable in both qualitative and quantitative research. However, this list is not complete, as tools and techniques continually evolve and new tools and techniques keep emerging in M&E. The list is adapted from ‘Project/Programme Monitoring and Evaluation (M&E) Guide from the International Federation of Red Cross and Red Crescent Societies (IFRC), 2011.’ The most common qualitative data collection methods and tools
The most common quantitative data collection methods and tools
Why a mixed method approach might be your best option for data collectionEach data collection tool and method has its own advantages but development projects are complex and their intricate dynamics cannot be disentangled through one method or one data collection tool alone. Therefore, mixing qualitative and quantitative methods and using different data collection techniques is recommended as it could add value to the monitoring and evaluation of your development projects. Using a combination of quantitative and qualitative methods, which is often called a mixed-method approach, enables researchers to gain a more holistic understanding of the intervention and why it is or it isn’t manifesting the expected outcomes. It also addresses the shortcomings and limitations of each method to provide more coherent, reliable and useful conclusions and increases the overall confidence in the validity of the evaluation results. Using mixed methods helps to capture a wider range of perspectives and in some cases, one method can be used to help guide the use of another method, or to explain the findings from that method. You can measure what happened with quantitative data and examine how and why it happened with qualitative data. Qualitative methods also help to uncover issues during the early stages of an intervention that can then be further investigated using quantitative methods, or quantitative methods can highlight particular issues that can be examined in-depth with qualitative methods. Some may point out that mixed methods could be costly and time-consuming but research shows that the benefits almost always far exceed the costs. Want to learn more about mixed-method approaches? Check out this World Bank’s document on “Combining Quantitative and Qualitative Methods for Program Monitoring and Evaluation: Why Are Mixed Method Designs Best?” We hope you found our article on qualitative and quantitative data collection methods helpful. As you see, both methods have their own advantages and disadvantages but when used in a balanced combination, they can really provide reliable evidence to unfold the progress and shortcomings of your development projects and help you make data-driven decisions for timely improvement and enhancement. However, the choices of methods depend on the nature of your project. But one thing to keep in mind, no matter which approach you may choose to utilize, it is important to observe the ethical principles of research for all data collection methods and tools. For more on the ethics of data collection, check out this short report by INTRAC – Principles of Data Collection. Key References
By Chandani Lopez Peralta, Content Marketing Manager at TolaData. |