Learning Analytics Principles and Policy
All staff members and students of the University.
To direct the development and use of all learning analytics at the University.
Fundamentally, learning analytics is concerned with combining data from different sources regarding student engagement and learning (e.g. data generated by learning management systems, student systems, library systems, prior learning and other sources related to learning and teaching) in order to better understand, and improve, the learning experiences of our students. They may also support pastoral care of students.
Learning analytics can be particularly valuable when teaching at scale, or online, where it can be more challenging for teachers to know how individual (or groups of) students are learning.
The development of learning and analytics activities must be guided by the following principles;
- Our vision is that learning analytics can benefit all students in reaching their full academic potential.
- All uses of learning analytics must be ethical, transparent and focused on the enhancement of the student experience.
- As an institution we understand that data will always provide an incomplete view of students’ capacities or likelihood of success. When data is used to inform action at an individual level it will always be accompanied by personal intervention by University staff.
- We recognise that data and algorithms can contain and perpetuate bias and we will work to avoid this.
- Good governance will be core to our approach, to ensure learning analytics projects and implementations are conducted according to ethical principles and align with organisational strategy, policy and values.
- We will be transparent about how we collect and use data.
- We will ensure that any notices we provide to students about learning analytics are consistent with the University’s Privacy Statement.
- The University is committed to relationships that acknowledge the principles of the Treaty of Waitangi.
Note - All learning analytics must comply with the University’s Privacy Framework, which assists the University to manage personal information in compliance with the Privacy Act and the privacy promises the University has made to students.
1. Overall responsibility for learning analytics at the University is held by the Deputy Vice Chancellor, Academic.
2. The University will use appropriate governance to oversee the development and use of learning analytics through the Analytics Working Group and the Data Governance Committee.
3. Responsibility for relevant areas of activity is allocated as follows:
- The collection of data to be used for learning analytics – Director Academic Services
- The analytics processes to be performed on the data, and their purposes – Deputy Vice Chancellor, Operations
- The use of learning analytics data for learning and teaching purposes – Director of Learning and Teaching
- The support interventions to be carried out on the basis of the analytics - academics and support staff supporting courses - Service Division staff in student support roles
- The retention and stewardship of data used for and generated by learning analytics – Deputy Vice Chancellor, Operations.
- Advice on impact of learning analytics activities on compliance with the University’s Privacy Framework – Privacy Officer
4. Students will have the option to opt out of automated communications generated by student analytics processes.
The following definitions apply to this document:
Learning analytics is ‘the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs’ (Society for Learning Analytics Research, 2012).
Staff member refers to individuals employed by the University on a full or part time basis.
University means the University of Auckland and includes all subsidiaries.
Key relevant documents
Include the following:
Document management and control
Owner: DVC (Operations) & Registrar
Content manager: Chief Digital Officer
Approved by: Vice-Chancellor
Date approved: 10 September 2019
Review date: 10 September 2022