Steps of Data Collection
Having reviewed the five approaches to qualitative research, Maxine begins to move on to teach Jonathan the basics of qualitative data collection. She emphasizes to Jonathan that the purpose of data collection is to gather good information to answer a research question(s). Data collection is a process comprised of 7 general steps or procedures. Thinking through these steps during the planning stages of a study can help to prevent unnecessary problems and ensure smooth execution of the study design.
Process of Data Collection
Locating site/individual
Selecting the right person, people, or group for study is critical to answering a qualitative research question. Take the time to think through questions such as, who will you study? What makes a person an appropriate participant for your study? Are all participants located at a single site or from multiple sites?
Gaining access and making rapport
Determine the best way to approach or access the study participants and how to build a relationship and establish trust with those individuals. Proceed with ethics in mind; seek permissions from IRB and establish procedures to ensure informed consent. Questions to consider include: do I need a gatekeeper to make introductions? Do the study participants have a history or previous experience with a research study? If so, what are his/her/their attitudes towards research?
Purposefully sampling
Purposive sampling is the non-random (non-probability) selection of individuals and sites because they can inform an understanding of the research problem. Common types of non-random sampling techniques include:
Convenience samples
Non-representative groups of subjects selected because they are the easiest to access. Study subjects are selected on the basis of convenience and not because they are representative of the entire population.
Purposive samples
Non-representative subsets of some larger population, constructed to serve a very specific need or purpose.
Quota sampling
Non-probability sampling technique wherein the assembled sample has the same proportions of individuals as the entire population with respect to known characteristics, traits, or phenomenon.
Extreme or deviant case selection
Used to obtain information on unusual cases.
Maximum variation cases
May be selected to obtain information about the meaning of different circumstances.
Paradigmatic cases
Selected when the desire is to develop a metaphor or establish a school for the domain that the case concerns.
Criterion sampling
Non-probably sampling technique where in the selected sample meets some predetermined criterion of importance (Patton, 2001, p. 238)
Additional resource: Miles & Huberman (1994, p. 28) - Miles MB, Huberman AM. Qualitative Data Analysis: A sourcebook of new methods (2nd ed.). Thousand Oaks, CA: Sage, 1994.
Collecting data
The most basic methods of information collection are interviews, observations, and document/audiovisual material review. New forms of data emerge all the time (e.g. blog posts, social media posts, emails, text messages, photovoice). There are methods that are commonly used for each of the five approaches, however a researcher is not limited to the common methods. Each method has advantages and limitations that must be considered when deciding which to use.
Recording information
Determine the best and/or most appropriate way to record data. It is good practice to audio record conversations and interviews, for the purpose of transcription and data analysis. However, participants must consent to being recorded. Traditional pen-and-paper records include pre-designed forms to record information during observation periods or interviews. Using forms, as opposed to blank pages, enables organized note-taking and focus on the participant/situation.
Resolving field issues
It is important to think through and anticipate in advance possible field issues that may arise during different points of data collection (i.e. entry and access, types of information collected, and ethical issues) so that solutions can be developed in advance and available to implement, if issues do arise.
Storing data
Storage of data will vary depending on the type of information collected. IRB requires that the researcher explain how data will be stored and protected. Basic principles of data storage and handling include:
- Backup computer files
- Use of high-quality audio recording devices and testing devices in advance
- Develop a master list of information collected
- Mask identifying personal information of participants