In the last blog post, we discussed what data are and why data are important. We defined data as information in its raw form. But where can you get data? Data is easily accessible and widely available if you know where to look. The first thing you might want to consider is what kind of data you need. For example, do you need student data, classroom data, or school-level data? This is a really important step to consider because these streams of data come from different places.
Student data can come from a classroom teacher, and this data can exist in a number of varieties like attendance records, test scores, or frequency of class participation. Classroom data can also come from a teacher, but this data often requires a bit more processing. If you are interested in classroom-level data, then you are probably considering the classroom as a single entity made up of all the students in that classroom. If this is the case, you need to find a way to aggregate, or put together, all of the “parts” (i.e., students) to make the “whole” (i.e., the classroom). In the next post, we will discuss some ways to work with data that help to address this issue and a few additional ones. School-level data often comes from the school district. One place in which to get school-level data is Nevada Report Card (nevadareportcard.com). Nevada Report Card is a great resource to get school data about the overall student population, standardized test performance, attendance, and graduation rates for a given school. However, it is extremely important that I take this opportunity to reiterate a note of caution from the last post: data are only as good as the degree to which you can explain where they come from and what they mean. If there is any data you, as an education professional, do not feel comfortable interpreting because you can’t understand what it means or where it comes from, don’t use the data until you seek out those answers. This does not mean that the data is not worthwhile; it just means that some clarification are needed before moving through any decision making process.
The sources for student, classroom, and school-level data provided above are not exhaustive, but rather serve to highlight some examples of where you might find data. But what happens if you can’t find what you are looking for, or if you need to collect more data? Data can be collected in a variety of ways, and this is often dependent on what kind of data you need and how much time you have to collect data. Your first step should be to try to articulate what you need to know. This is a really important step to planning your data collection process. This first step is different than identifying your problem that you want to answer (you’ve probably already done this, which is why you decided you need more data). Instead, in this step, you are trying to identify the pieces of information that you need in order to answer the problem. If you aren’t sure exactly what data would be helpful, it might be best to talk to and work with others that might also have a stake in that problem. Next, you need to figure out where to get the data you need. At this point, you may consider going to that person (i.e., classroom teacher or administrator) to work together with them. Collaboration goes a long way when you can persuade others that your need is a worthwhile endeavor that can benefit many in the long run. Then you need to consider what getting the data looks like, and this is where the issue of your time (and others) comes into play. Data collection can be a laborious process (and often the least exciting part of any research-type endeavor). When considering the time intensity of data collection, you might want to consider, for example, whether you want to ask a classroom full of students or all of the teachers at your school a set of questions individually (highly time intensive), or whether you want to set up an online survey that can be emailed out to everyone (much less time intensive). Another example could be asking a teacher to report student data on the results of every math problem on an exam versus the total score on the assessment. These examples, again, are not exhaustive, but serve to highlight different levels of time commitment and data intensity (more data versus less data). In the next post, we will discuss what to do with your data once you have it.