In our technology driven world, data about students can be collected from anywhere and anything. The type of data that is collected varies by the program that is being used, but usually it provides information about the frequency with which students’ access online materials or the results of assessments from student exercises and activities conducted online.We have placed the focus of our OER on two applications of learning analytics – trend analysis and prediction, and personalization and adaptive learning. Through these two applications we will learn how how learning analytics can be used by educators in the classroom and its potential improvements and challenges in learning.

The use of learning analytic tools can help educators collect more information about individual students than ever before to help personalize their learning and identify factors that have a positive or negative effect on learning. Learning analytics is drawing attention in education as it can provide suggestions and predictions for future success in learning for individual students. Yet can we predict how successful learning analytics will be in an educational setting?

Throughout this week there are four activities to complete. If at any point you are unsure that you completed all activities please head over to the “Checklist“ to double check.

Now let’s get started!

Please continue on to “Overview“ to complete Activity #1.