When thinking of a dissertation or thesis question, you must also think about the research design. A testable question regarding angels is "Do people believe in angels? As an example, your survey might simply ask "Do you believe in angels? This is not an empirical question and it's not going to give you much data, but it's one that can be answered in a dissertation.
An empirical question could be "What influences a person's belief in angels? For example, other dissertations may have found that more women than men believe in angels. You might also find a dissertation that reported Catholics believe in angels more often than atheists do. A third research might have reported that people are more likely to believe in angels if the people in their social circles do.
So, how would you design an experiment to answer the question "What factors influence a person's belief in angels? What if you asked "Does watching a news story about a person's encounter with an angel influence their belief in angels? Combine it with a bunch of demographic information from your subjects and you may have a good dissertation. One group could be shown a news story about a person who claims they saw an angel.
The subjects in this group, the experimental group, then complete a survey. The other group, the control group, does not see the news story, but completes the same survey. What do you include in the survey? Good data collection involves collecting relevant data that adds to the body of knowledge. Knowing that people who believe in angels also eat spaghetti is not particularly useful nor important.
The main thing to remember with data collection is to keep it simple, but important. And get the data you need the first time out! There's nothing more frustrating than realizing you could answer an important question if you added just one more variable. For this research design, you could collect demographic information thought to be associated with your dependent variable belief in angels.
Age, gender, religion, ethnicity, social network, and frequency of church attendance may be just a few. But how are you going to measure these variables? Are they dichotomous variables? Self-report is a type of research design in which participants give their responses to a given set of questions. The most common types of self-report are interviews or questionnaires.
One major limitation of self-report versus other data collection methods is that accuracy of responses cannot be determined, and there are many circumstances in which participants are likely to lie.
Observation is a method of collecting data in which members of research teams observe and record behaviors. Data collected during observation are explicit and quantifiable. However, observation has many limitations. First, researchers who use observation can only observe behaviors; therefore, observation cannot be used to collect data about attitudes, beliefs, thoughts, covert behaviors, etc.
Another limitation of observation is that it is a known fact that being observed changes behavior. Observation can be either formal e. These types of data are useful because they are quantifiable and accurate.
However, these types of data are sometimes used as secondary measures of latent constructs, which may not always be accurate. For example, someone with a high heart rate may be perceived as being anxious, but it is possible that that person just walked up a flight of stairs.
Interviews are one of the data collection methods for qualitative research. Interviews consist of meeting with participants one on one and asking them open-ended questions. Interviews can be structured or semi-structured. In a structured interview, the researcher has a predetermined set of questions to ask and does not deviate from those questions.
In a semi-structured interview, the researcher will have prepared questions but has the freedom to ask additional follow up questions as he or she sees fit.
Success of conducting research depends over the result that is gained by the researcher at the end of the research. These attained results are affected by the used methods to conduct research. In this way, there are two type of methods are available to collect the data to reach at the result of the research [ ].
Data Collection for Dissertation & Thesis Research When collecting dissertation or thesis data, there are numerous things to consider. First, you must develop a good idea.
Regardless of the topic of your dissertation or thesis, it is highly likely that at some point you will need to collect data. Below are some common data collection methods. STEP SEVEN Data analysis techniques. In STAGE NINE: Data analysis, we discuss the data you will have collected during STAGE EIGHT: Data directlenders.mlr, before you collect your data, having followed the research strategy you set out in this STAGE SIX, it is useful to think about the data analysis techniques you may apply to your data when it is collected.
PDF | As it is indicated in the title, this chapter includes the research methodology of the dissertation. In more details, in this part the author outlines the research strategy, the research. An overview of the considerations required when undertaking data collection for a replication-based dissertation.