Learning analytics is the measurement, collection, analysis, and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs (SoLAR, 2011).

The prevalent use of digital learning materials and academic technology generates a massive amount of real-time course interaction data. This  data is becoming more accessible to the instructors who design and implement courses in higher education. This interaction data is often more detailed than traditional educational data and has the potential to provide insights into student learning processes.

Typically, performance data (i.e., grades) and student feedback are used to determine course effectiveness, but these are limited in terms of understanding the actions that students take. Learning analytics that integrate a wider variety of student learning data from multiple sources can inform our understanding of what happened, what led to certain outcomes, and what future actions may foster student success.

By leveraging learning analytics, Research and Analytics provides insights into how students engage in your course and what course engagement and activities are associated with various learning outcomes. The following are sample questions we can help you answer:

  1. Is a recent change in your course design having the outcome you intended?
  2. Which learning activities/tasks are most critical for student success?
  3. Do your homework assignments and quizzes align with your exams?
  4. What is a realistic expectation for use of the academic resources you provide over the course of a semester?
  5. How are students engaging with learning tools such as ICON, UICapture (Panopto), Top Hat, and eText platforms?

If you are interested in learning more about how learning analytics can help your teaching and your students’ learning, please contact us at its-ra@iowa.uiowa.edu.

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