One of the most ~daunting~ things about research is that everything you do early on has significant ripple effects for everything later on. Your sample, or who you choose as participants, is really important because it determines the data you will be able to collect and how reliable your results will be. If your sample is very narrow–everyone in it is very similar–your data will only tell you about that type of person. If the sample is too broad or imbalanced, it will be difficult to draw conclusions based on variables related to the people in the sample. For example, if you have a sample of 10, 8 women and 2 men, the data you collect will not be reliable in relation to men.
We have decided that our primary variable is the amount of information literacy intervention the student has had, which also generally corresponds to degree level. We’re also interested international students and first-generation college students. The plan is to pull a quota sample that equally represents all of these major characteristics. At the end of day, I’m not sure that there will be significant differences along the lines of international and first gen students, but I do believe it’s vitally important that those students are represented in this research. There is a phenomenon in social science research that participants tend to be white, educated, and high-achieving; it’s important to actively combat that.