45 Learning Analytics
Learning Analytics
Learning analytics is part of the “big data” conversation. In essence, the strategy implies that we do three things:
- Assess students early, often, and meaningfully in a course — including assessments of non-graded motivational indicators, such as logging into the course website and doing ungraded practice problems (for example);
- Identify those students who, at every assessment moment, fall below a threshold for understanding or engagement; and
- Quickly and efficiently stage meaningful interventions for those students who are struggling to help them get back on the right track.
This strategy is powered by the fact that, increasingly, our assessments and course activities are conducted in a digital context.
D2L Brightspace offers various ways for you to track learners’ progress. While MNSU does not yet have a data analytics package, there are some tools you can use to contribute to the overall picture of student success:
- Adding Competencies and learning objectives
- Using the Rubrics tool
- Tracking student progress through the Class Progress or User Progress Tool (in Classlist)
