methods of data collection
Data collection methods for impact evaluation vary along a range. At the one end of this range are quantitative methods and at the other end of the range are Qualitative methods for data collection.
The Quantitative data collection methods rely on random example and prearranged data collection instruments that fit various experiences into predetermined response categories. They produce results that are easy to sum up, evaluate, and simplify.
Qualitative data collection methods play an vital role in impact estimate by providing information useful to understand the processes behind experimental results and assess changes in people’s perceptions of their well-being. Furthermore qualitative methods can be used to get better quality of survey-based quantitative evaluations by helping produce evaluation suggestion; strengthening the design of survey questionnaires and expanding or descriptive quantitative evaluation finding
Quantitative research is worried with testing hypotheses derived from theory and/or being able to approximation the size of a phenomenon of interest. Depending on the research question, participants may be arbitrarily assigned to dissimilar treatment. If this is not possible, the researcher may collect data on member and situational characteristics in order to statistically control for their influence on the dependent, or outcome, variable. If the intent is to simplify from the research participants to a larger population, the researcher will employ probability example to select participants.
Typical quantitative data gathering strategies include:
Observing and recording well-defined events
Obtaining significant data from management information systems.
Administering surveys with closed-ended questions
They tend to be open-ended and have less structured protocols.
They rely more deeply on interactive interviews; respondents may be interviewed several times to follow up on a particular issue, clarify concepts or check the reliability of data
They use triangulation to increase the reliability of their findings (i.e., researchers rely on multiple data collection methods to check the genuineness of their results)
Generally their result are not generalizable to any exact population, rather each case study produces a single piece of confirmation that can be used to look for general pattern among different studies of the same issue