Learning Analytics

The primary focus of Learning Analytics in Nuku is to provide actionable information to support students and to encourage improvement of teaching practices.

Find out how you can use your students' learning data in Nuku to understand their engagement patterns and support student learning in your courses.

Review the University Learning Analytics Guidelines

Potential Benefits of Using Learning Analytics

  • Identify students at risk (at different stages of the course) to initiate interventions and provide timely support
  • Make students feel ‘seen’ in a large course by recognizing their achievements and challenges
  • View average grade and grade distribution for any assignment/s to understand student learning patterns in progress
  • Check student course activity to identify and mitigate learning slumps
  • Understand how course resources and assessment items are used by students, in order to improve their effectiveness
  • Evaluate and improve the efficacy of the course design

What can I use LA tools for?

Check if students are “present” in the Nuku course

  • Students are given a task/activity that requires them to visit their Nuku course site within the first two weeks of the course start.
  • There is a formative (low-stakes) assessment item that students are required to complete by the end of week 3.

Counteracting the “mid-trimester slump” 

  • Create an activity or task for students to complete in Nuku after the mid-trimester break to check that students are still engaging with the course.

Take the learning pulse: check how students are “learning”

  • Use quizzes or low-stakes assessment that can help you answer the following questions:
    • Have students understood key course concepts?
    • Can students apply their new knowledge?

[See also: Threshold Standards for the Online Student Experience ]

What actions can I take to support my students?

  • Develop a consistent (e.g., programme level) approach to sending messages to students about their course behaviour and performance
  • Contact students at risk of disengagement with the course
  • Contact students to facilitate timely assessment submission
  • Send positive messages based on student participation and their academic performance


  • Be specific in your communications with students, offer help and support (e.g., suggest additional readings and/or individual support options, if appropriate)
  • Work with Tītoko student advisers when students do not respond to or act on communications, or when more holistic support is needed.

Disclaimers and Warnings

  • Learning analytics tools do not provide a comprehensive picture of student learning or engagement
  • Caution needs to be taken in drawing conclusions about student learning, based exclusively on the Nuku data
  • Learning analytics reports need to be validated against other data sources and factors that may affect student behaviour.

IMPORTANT: the best way to interpret a student’s data is to invite that student to interpret it (just ask!)

IMPORTANT: Nuku learning analytics must not be used as a basis for reducing a student’s course grade or declining a requests for an extension (or similar).

Watch an online Introduction to using LA in Nuku