Performance Analytics

This week I wanted to return to the idea of data-driven learning design from earlier in the course. We are in the process of designing a Learner Dashboard at work (which will hopefully be developed and added to our LMS). For months, this Learner Dashboard was discussed in the abstract as the ultimate tool for tracking student progression and performing Continuous Quality Improvement. This week, we finally sat down and starting to discuss what exactly the Learner Dashboard needed to be. 

The discussion was interesting because it required us to define performance indicators and the data that we need to collect in order to get a complete view of the student and of the curriculum and course design. It also highlighted the importance of defining two types of performance indicators:

#1 – indicators to measure the success of the student
#2 – indicators to measure the success of the learning experience

The conversation was really interesting because we needed to starting thinking about the distinction between what we can measure and what we should measure. 

The concept of digital body language will need to be a key part of this conversation as we continue to develop this concept; it’s clear that we are able to collect a ton of information about our users, but much like the important of “Why?” in making design choices, we really need to understand the “So What?” of analytics. 

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