#DALMOOC Definition of Learning Analytics

Competency 1.2: Define learning analytics and detail types of insight they can provide to educators and learners.

If you’ve been tuned in but I’ve been absent, my apologies for the series of posts coming up which all pertain to the edx.org Data, Analytics, and Learning MOOC which is being run out of UTx October through December. The text below is my personal definition of learning analytics and what they can provide educators and learners.

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Student created data captured within a learning management system or one a site is valuable insight and information that can be leveraged to improve student success through both automated and human-initiated outreach to student. In aggregate it represents the digital experience of a student on a site, detailing their progress through designed learning experience and can be directly connected to success (or lack thereof) on examinations and assessments (especially objective assessments). In my definition I’m leaning more towards (and interested more in) the use of this data for institutional change by improving the experience at the student level. Rather than focusing only on the student level.

While the definition identifies the term as a noun, it can be acted upon by both educators and learners to improve the status of the current or potential learner through course improvements, proactive messaging, automated reminders, scaffolded materials, improved experience and course design,… Through the data I can learn how different student segments are achieving. The profile of a student modeling exactly the behavior I want, if students are using resources as intended (or not), impact of new or different resources, competency and success, and learner satisfaction.

The goal of using insight is to improve the student experience focusing on success, satisfaction, efficiency, and effectiveness.