Data interpretation
NEW: A vision for education and skills at Newcastle University: Education for Life 2030+
Data interpretation
Interpreting the data presented by NULA requires a thoughtful analysis of the various metrics, such as Canvas engagement, attendance, submissions, and attainment, in order to gain a holistic understanding of a student's engagement with their studies.
In the resource below, you will find four case studies, each featuring screenshots of sample student data from the system. As you review each case study, consider the following questions:
- What inferences can you draw about the student’s performance and engagement with their course?
- Are there any noticeable trends or patterns in the data?
- How can this information be used to provide support to the student?
After examining each case study, a brief video will discuss potential insights from the student data, highlighting key trends and data points.
