Technology is supposed to aid instructors with their courses, but with the increasing amount of data generated by laptops, smartphones, tablets and Learning Management Systems, so much data can seem like a vast, confusing sea of information. How can we navigate past the rocks and shoals and steer ourselves into calmer waters where we can put the data to use?
Learning analytics deals with the analysis of large data sets to enhance instructional, curricular and support resources. The area of learning analytics is rapidly gaining momentum across institutions and allows us to not only describe trends but also help prescribe solutions and predict future outcomes.
Learning analytics can aid in predicting future student performance and flag students who might be struggling. They can also help personalize learning processes so you can adapt your teaching style, assignments and content to more appropriately challenge students.
“That’s great!” you say, but “how can I put learning analytics to work for me?” Well we’re glad you asked, but since there are so many applications, we’re just going to list a few top-of-mind ones here:
- First off instructors using ANGEL can monitor how often your students are logging in, how long they’re staying logged in and what resources they are using. From this information you can see if students are using resources you’ve added. Take it one step further and you can see if those that accessed certain materials more often received better grades.
- For those links that you send outside of ANGEL, you can use a URL shortener to track how many people are actually clicking on the link. If you send the link in an email, it doesn’t make a difference if you put it at the beginning or the end of the message.
- We know how important logging in during the first days of class are for online classes, why not create an ANGEL login report that shows who has logged in since the start of class.
Whew! Ok, so that sounds like a lot to swallow, but over the course of time as more data is collected and the predictive modeling for classes and individual students is refined, learning analytics should become a second nature practice for most faculty.
There is so much more to learn about learning analytics that we’ve shared a few links below to get you started. But if you’re already utilizing them in the way you run your courses, or have any innovative ways on how to apply them, we would love to hear from you so we can share your insight with your fellow faculty members.
Take a look at this infographic on learning analytics for a visual representation of the subject.
Here you will find a comprehensive report about the use of analytics in colleges and universities: 2012 ECAR Study of Analytics in Higher Education
You will find several links to a multitude of materials about analytics on this Educause page.
When Learning Analytics Meet Big Data – The Predictive Analytics Reporting (PAR) Framework” – Educause 2012 Annual Conference – Denver, CO – 11/8/2012 (Video Presentation)