Outlining a Data Collection Plan
The purpose of outlining a data collection plan is to describe the methodology you will use to collect data that will further assist you in evaluating the alternatives under consideration. You will collect data that you can use to determine whether your “Hypotheses” are supported and to answer the other research questions you have developed. In Chapter 3 of your study, the methodology, you outlined what you believed to be the perceptions regarding the advantages and disadvantages of each alternative. Your intention now is to collect data that will test or verify those perceptions.
Mechanics of Data Collection
In order to collect the data needed to carry out your evaluation, it will be necessary to construct a survey or questionnaire or some other data collection instrument. Frequently utilized approaches to collecting data include:
- random sampling
- focus-group interviews
- in-depth interviews
- cluster or area sampling.
If you are surveying human subjects, please adhere to your University Policy on Human Subjects.
Before constructing a questionnaire or developing some other form of data collection procedure, it is necessary to establish hypotheses. A hypothesis is a tentative, educated guess that suggests a possible explanation for why a specific problem exists. It is different from an assumption in that an assumption represents a condition that is taken for granted. In other words, a hypothesis is an assumption that can be subjected to a test of its validity. For example, when your department fails to achieve its objectives, you may assume that it’s because the employees aren’t meeting their individual goals. After deciding to research the problem, you want to put your assumption to a test: Is it valid or invalid? After some preliminary analysis and review, you develop a hypothesis about the situation: If the sales staff were better trained, they would feel more confident, have better skills, and work harder to achieve their quotas. Now this is still just a refined assumption until you test it. One way to test the validity or invalidity of your hypothesis is to survey a group (population) of employees; you would ask them about the role training plays in their personal success.
Keep in mind, however, that hypotheses are neither proved nor disproved. Nevertheless, you can collect data that will either support or not support your hypothesis. The results of your survey, for example, may overwhelmingly show that successful employees credit training as a major part of their success. From this, you might be able to conclude that your department could improve its results by initiating additional training programs. If, on the other hand, the data you’ve collected does not support your hypothesis, you shouldn’t let that disturb you. It just means that your educated guess as to what the survey results would show was wrong. Frequently, unsupported hypotheses are a source of genuine and gratifying surprise for the researcher. Now you have some data that indicates that your preconceived notion about the situation is perhaps in need of reappraisal.
Establishing hypotheses is essential to designing a well-focused data collection procedure. Once you have determined your hypotheses, it becomes possible to formulate questions that will help you decide whether or not your hypotheses are supported. The example hypothesis, “If the employees were better trained, they would feel more confident, have better skills, and work harder to achieve their goals,” suggests certain questions to ask in order
to test its validity. Make sure that the data you collect is related to your hypothesis.
Your written description of the data collection methodology used should include descriptions of:
- the data collection design utilized;
- the population being studied—state the size of the population and how individuals were
selected and assigned to groups;
- the data collected, including demographic data about the sample population;
- when and where the data were obtained and the manner in which they were obtained;
- any special precautions taken to remove bias in the data collection process;
- the methods used to analyze the data;
- any limitations which exist in any part of the data collection plan;
- how you constructed your questionnaire or its source and whether or not you tested it before it
A copy of your data collection instrument should be included in an appendix.