Data collection is the first stage in the research process. Data collection, usually occurring simultaneously with data analysis in qualitative research, is defined as the systematic gathering of data for a particular purpose from various sources, including, interviews, focus groups, observation, existing records, and electronic devices. Depending on the data collection method, researchers could encounter challenges with obtaining information from participants in a study.
Researchers wish to obtain valid and accurate data for rational finding. Survey is designed to obtain information about the prevalence, distribution and interrelation of phenomenon (Polit, & Beck, 2012). Therefore, researchers must design a well-structured plan to anticipate every challenge faced in the field where research takes place in order to produce valid and accurate data.
Methods used to collect data vary based on the type of application. Some involve the use of technology, while others are manual procedures. The following are some common data collection methods:
- Automated data collection functions built into business applications, websites and mobile apps.
- Sensors that collect operational data from industrial equipment, vehicles and other machinery.
- Collection of data from information services providers and other external data sources.
- Tracking social media, discussion forums, reviews sites, blogs and other online channels.
- Surveys, questionnaires and forms done online, in person or by phone, email or regular mail.
- Focus groups and one-on-one interviews.
- Direct observation of participants in a research study.
Well-designed data collection processes include the following steps:
- Identify a business or research issue that needs to be addressed and set goals for the project.
- Gather data requirements to answer the business question or deliver the research information.
- Identify the data sets that can provide the desired information.
- Set a plan for collecting the data, including the collection methods that will be used.
- Collect the available data and begin working to prepare it for analysis.
Some of the challenges often faced when collecting data include:
- The period of data collection poses a threat to the success of the data gathering process. The data gathering process can be negatively affected by the time span of the data collection instrument or how time-consuming the data gathering process is (Rimando, et al., 2015). Lengthy questionnaires or interviews can create discomfort for respondents. Their discomfort may lead them to provide inappropriate responses to questions asked in questionnaires or interviews. In some cases, respondents may provide information that is of no use as they hastily partake in the data gathering process (Rimando, et al., 2015). Lengthy questionnaires or interviews can result in thirst and hunger of the respondents. It is advisable to make provision for hunger and thirst, especially, if the researcher is aware of the lengthy period of data collection. For instance, the researcher can provide furniture, water and cocktails for respondents before accomplishing the survey (Dearnley, 2005; Easton, McComish, & Greenberg, 2000).
- Researcher tiredness is one of the hindrances to data collection for qualitative research. Conducting focus groups and interviews can be stressful for the researcher who is collecting the data. Researcher exhaustion is a key element to the smooth flow and achievement of successful focus groups and interviews (Dickson –Swift, James, Kippen, & Liamputton, 2007 ; Fern, 1982). This implies that researcher fatigue can reduce the quality of data. The onus is on the researcher to manage the fatigue associated with focus groups and interviews in order to ensure data quality. Researchers have to be observant, study people, listen attentively, and handle diverse personality types (Fern, 1982; Kreuger, & Casey, 2009). The researcher has the duty of enticing the quiet participants during focus groups so that every participant gets the chance to contribute. Fatigue can undoubtedly influence the researcher’s competence to effectively handle interviews and focus groups. Unless the researcher is firmly in charge of the meeting, the conversation could digress into irrelevant matters, possibly squandering participant’s precious time (Orvik, Larun, Berland, & Ringsberg, 2013).
- Insufficiently trained staff. It is important to provide training to staff involved in the collection of data. Training should emphasize why it is important to collect data and highlight the benefits of data for operations, planning, research and evaluation. If staff understand the rationale for collecting certain information, they will feel more confident to ask for these data items and to explain why it is important. Role play various situations in which the team may or will find themselves: gaining approvals from authorities, giving explanations to community leaders/teachers, implementing surveys, fielding questions from respondents, etc. Training should include how to phrase questions, clarify answers and record responses.
- Dealing with big data. Big data environments typically include a combination of structured, unstructured and semi-structured data, in large volumes. That makes the initial data collection and processing stages more complex. In addition, data scientists often need to filter sets of raw data stored in a data lake for specific analytics applications. Common big data challenges include: You can’t easily find the data you need. You’re collecting inaccurate and/or outdated data. Data security and protection are overlooked. Shortage of qualified personnel in big data analytics.
- Language comprehension barrier. Language is needed for any kind of communication, even people with speech impairments communicate with sign language and braille. Communication becomes difficult in situations where people don’t understand each others’ language. Consideration: Hire professional translators to translate questions and then have another translator back-translate to the original language to ensure intended meaning is not lost. Pilot test the survey with a variety of people to ensure intent is understood.
- Literacy comprehension barriers. Reading is an interactive process in which the writer and the reader dialog through a text. Barnett (1989, cited in Omaggio, 1993) defines reading as communication, as a mental process, as the reader’s active participation in the creation of meaning, and as a manipulation of strategies. Moreover, Day and Bamford (2000) posit that reading is the construction of meaning from a printed or written message. Consideration: Survey responses can be read to participants. Mobile devices can also be utilized to ‘read’ to respondents who select non-read response options (face expressions, colors, etc.).
- Informed Consent. Researchers must educate and inform their targeted populations about the nature of their studies. They should also inform the individuals about the potential benefits and risks of every study (Fouka & Mantzorou, 2011). Sometimes it is impossible for researchers to obtain the required consent from different groups. Consideration: Every survey will require approvals at one stage or another. Adult respondents must agree to be a part; child respondents must have their parents’ approval. If conducted in school or in any organized environment, educators/leaders will need to approve the endeavor. Ensure sufficient time is built into your timeline to acquire all necessary approvals.