The 4 Levels Of Learning Analytics

Using data to drive learning outcomes isn’t a new concept, really. For as long as teachers have been giving students assessments, the assessments and results have been used by both students and teachers (even if only loosely) to determine how to move forward. What needs to be reviewed more? What was covered/studied well? Learning analytics takes this concept and kicks it up a notch. Well, more like a thousand notches, especially if you’re considering things like adaptive computer based testing that changes as students use it.

The handy infographic below takes a look at the four levels of learning analytics, which can be easily applied in your classroom whether you’re using a ton of fancy-schmancy technology or none at all. Take a look and tell us what you think: Do you use the four levels of learning analytics to drive change and learning in your classroom? Do you do it with technology or without? Join in the discussion by leaving a comment below, mentioning @Edudemic on Twitter or leaving your thoughts on our Facebook page.

The 4 Levels of Learning Analytics

  1. Descriptive: What has happened? Look at facts, figures, and any other data you have that give you a detailed picture. Did a student fail a math quiz? What concepts were mastered and what ones weren’t?
  2. Diagnostic: Why did it happen? Examining the descriptive elements allows you to critically assess why an outcome happened? The student did ok on geometry questions but bombed the algebra-based material? Was less class time spent on the algebra stuff? Were different types (or amounts) of homework given? Look for explanations
  3. Predictive: What will happen? This is where you look forward: What would the outcome be based on different elements. Think of it as a choose your own adventure – will the student learn the algebra based material better if X, Y, or Z happened?
  4. Prescriptive: What should I do How can a specific outcome be achieved through the use of specific elements? Take what you’ve learned through 1, 2, and 3 and apply it in an effort to achieve the learning outcome you’re looking for!

 

Learning-Analytics

1 Comment

  1. norbert boruett

    July 10, 2014 at 3:20 pm

    Learning Analytics defined- this is powerful, it makes elearning powerful