Teaching staff: Learning analytics in my subject

Overview

Learning analytics can be divided into two types:

  • Subject-level learning analytics: Assists teaching staff in understanding their individual subject design and delivery (this page)
  • Faculty/school cross-subject learning analytics: Provides course co-ordinators, department heads, school or faculty leaders with insights into student experience and delivery across multiple subjects in their area (see learning analytics across my area - for faculty or school leaders).

This page details the learning analytics available at the subject-level. If you are wishing to use learning analytics data in your research see using learning analytics in research publications.

How can learning analytics help me identify students who may be in need of assistance?

Learning analytics acts as an early warning system by tracking real-time metrics like LMS logins, missed formative or summative tasks, and discussion participation. This visibility allows academics to identify students who are quietly falling behind long before mid-semester assessments occur.

How can learning analytics provide insights into student engagement with my subject?

Learning analytics provides concrete data on how your cohort interacts with subject materials, revealing metrics like video completion rates and viewing of modules and pages. By tracking interactions with active learning elements such as H5P interactive activities or formative quizzes, you can see exactly which resources capture attention and which are being missed or skipped. This evidence-based insight allows you to refine your curriculum to better align with actual student learning behaviour.

How can learning analytics help me understand and improve my teaching?

By analysing how students navigate your subject, learning analytics highlights the effectiveness of your design and delivery methods. If data shows students underperforming on tasks or consistently skipping certain modules, you can investigate exactly where their engagement or understanding is falling short to improve content clarity and accessibility. Ultimately, these insights empower you to make targeted, continuous improvements to your teaching strategies based on actual learner behaviour rather than assumptions.

What challenges do I have when interpreting learning analytics?

The primary challenge with learning analytics is remembering that data provides the 'what', but not always the 'why' behind student behaviour. A lack of online clicks does not automatically mean a student is disengaged; they may be reading offline, collaborating externally, or facing personal issues. Therefore, it is crucial to use learning analytics data as a prompt for conversation and further investigation rather than a definitive measure of student effort or capability.

What learning analytics do I have available to me?

Visit subject-level learning analytics available in Canvas and our educational technology tools to understand the different learning analytics available in Canvas and our centrally supported learning technologies.

Can I publish my learning analytics insights?

Visit using learning analytics in research publications for guidance on research and learning analytics.

Learning analytics to aid your academic career progression

Learning analytics can support your career progression and the annual Performance Development Framework (PDF) process by providing evidence of:

The Academic Performance Development Framework (PDF) provides details and documentation for academic career progression and PDF processes.