If you’ve read anything in the past few years, you’ve seen the uptick of the term “analytics” or “data analytics.” It’s such an important term that entire degrees have been formed around it. This might make it seem like data analysis is for someone else who specializes in interpreting data, but if you’re an instructor, you actually have a wealth of learning analytics available to you, and interpreting the analytics yourself can lead to a richer classroom environment.
The first place you can look for potential learning data points is on your school website (these are more inferences than information on what students have learned). For example, I typed in “student statistics” to my school search bar and I found information on new student test scores and high school GPAs. It also showed me the gender, ethnic, and location-based data for my school, as well as groups of data around Chapman retention rates, applicant selectivity, and scholarship awards. This data can help us to understand the basic student make-up before even stepping foot in the classroom. For example, based on the data, you might be able to infer that the students need extra support or that they have strong studying skills. My school also gives us access to our course-specific student demographic once students have registered for their courses, such as their year of school and their majors.
Once you’ve started teaching, the learning management system (in our case, Blackboard) can also gather a great deal of class-specific data. For example, Blackboard’s Retention Center and Performance Dashboard can give information about how often students are accessing the site, whether they have late assignments, and other information about grades and activity.
Blackboard Course Reports can also parse down a little more into course-related activity. These data points can help instructors track and support struggling students.
For even better learning analytics, I like to make a number of online multiple choice tests as either graded or even non-graded assignments. Whether these are done through an LMS or through another online platform (like Poll Everywhere), I like to harvest the information to see what specific points students are missing so that I can revisit the points that are necessary to make my students successful.
These potential learning data points are easy to come by and informative for any learning practitioner.
Another great read on the actions that can be taken from learning analytics to improve learning comes from Educause: Moving the heart and head: Implications for learning analytics research