Learning Analytics is the use of data and models to predict student progress and performance, and the ability to act on that information.
Learning Analytics Fundamentals
Learner data can be assembled by capturing learner interactions with:
- course and curriculum content (media, linked resources, simulations, lessons, units)
- asynchronous or synchronous communications and collaboration tools
- integrated social media, community and social learning
- assessment data and performance
- remediation and student support mechanisms
- intermediate and overall learning outcomes.
These fundamental interactions provide the basis for developing an effective learner and student profile from within a single course. However, Learning Analytics should not just capture components from within a single course of learning but also across the curriculum and/or program the individual is currently studying. Much can be gained however from the accumulation of such data from an individual course.
Correlations can then be built in support of providing instructors/teachers and students with the information they require for achieving student success. Ideally data automation and successful correlations can provide
The Gilfus Analytics team can develop a strategy around learning analytics for your organization