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4 Data Collection Methods

Desktop computer screen showing data collection method
Once you understand the difference between qualitative and quantitative data it is helpful to understand the variety of methods you can use to gather your data. Data collection methods are tools that help organizations collect quality data. When these tools are applied accurately, organizations can be confident in their data. The list below provides the most common data collection methods: 1) Focus Groups, 2) Interviews, 3) Observations, and 4) Surveys

Focus Groups
This data collection method involves face-to-face interactions between researcher/moderator and respondents. Typically, most of the data gathered within focus groups are qualitative in nature. One of the goals of focus groups is to get respondents to provide further details and insight into their opinions, something that is typically not available via quantitative data collection methods. Focus groups are great for understanding the why and what behind your questions. For example, through focus groups you can understand why people like your program or what they think about your idea.  Data collection during focus groups can be enhanced by the group dynamics/conversation between the respondents. If you need a reminder of what qualitative data is, please refer to one of our previous blog posts What is Quantitative and Qualitative Data?

Like focus groups, interviews typically gather qualitative data, rather than quantitative data. Interviews can be more focused or open-ended depending on the needs of the researcher (Thomas, Nelson, & Silverman, 2015). Since interviews are done on a one-on-one basis (either in person or over the phone), the researcher is looking at an individual’s opinion on something, rather than group discussion. It’s important during interviews that whoever is conducting the interviews builds a rapport with respondent, which in turn results in getting further details over other data collection methods (Thomas, Nelson, & Silverman, 2015).

Observational data collection methods include observing behavior in it’s natural state. There are two main types of observations that can take place: 1) participant observation and 2) unobtrusive observation. In participant observation, a “researcher may interact with participants and become a part of their community” (Driscoll, 2011). In unobtrusive observation, the researcher does not interact with the participants and instead takes notes about the behavior they are observing (Driscoll, 2011).

Surveys are a common type of data collection method. Surveys typically gather quantitative data, but can also gather qualitative data. Surveys can typically be collected online or with paper. Surveys tend to consist of predefined close-ended or open-ended questions that require some kind of response. Three main types of response options include: 1) categorical or nominal, 2) ordinal, and 3) numerical. Categorical or nominal data are data that have no numerical value, such as race/ethnicity or eye color. Ordinal data includes rating your response based on a scale such as a Likert scale. Most Liker scales include 4 to 7 responses. One of the most frequently used ordinal response options are: strongly agree, agree, neither agree nor disagree, disagree, and strongly disagree. In contrast to categorical or nominal data, numerical data is looking for a numerical response. Common numerical data include things like height, weight, age, and number of times you have done something (Taylor-Powell, 2008).

This REC 5-part blog series started with a post entitled Collecting Quality Data – 4 Questions. The final blog post will focus on the pros and cons of the various data collection methods mentioned here. Hopefully, reviewing the pros and cons of these various methods will help you make the best decision for your needs. As you think of which method will get you the data you need, think about how you plan to use and report this information.  This consideration will help you decide which method is best for you!

Feel free to contact me with any research and evaluation needs: annette@researchevaluationconsulting.com

3 Responses so far.

  1. nice share! it’s also necessary to implement offline data collection feature that syncs the information automatically

  2. Dark Web says:

    Great info presented here. Highly Appreciated

  3. Fluix.io says:

    If we talk about the methodological features of ICT, then the main emphasis is on such an important feature of the integration of research approaches as combining their advantages and neutralizing disadvantages. Thus, studies of a mixed type allow: a) to carry out cross-validation of data obtained from various sources; b) exclude or minimize competing explanations and interpretations; c) clarify the contradictory aspects of the phenomenon under study [Johnson, Turner, 2003: p. 299].
    Burke Johnson and Lisa Turner (Johnson, Turner, 2003) identify 18 specific approaches to data collection based on six methods (survey, interview, focus groups, tests, observation, secondary data) and the research approach used (qualitative, quantitative or mixed) .. At the same time, various methods of data collection can be combined in two ways – intramethod or intermethod

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