Students: My data and learning analytics
Student data and learning analytics: How we use data responsibly
How Teaching and Learning Innovation and the University of Melbourne collect, use, and protect your learning analytics data. We are committed to responsible data management that benefits your learning while respecting your privacy.
Why we collect your data?
Learning analytics data collected in our learning technologies helps us enhance teaching quality, improve subject delivery and curriculum design, and manage assessments more effectively. By understanding your study experience and engagement patterns, we can continuously improve the overall student experience.
What learning analytics data is collected?
The University requires all supported learning technologies to complete a privacy impact assessment (PIA). This process reviews personal data management practices in each tool, ensuring compliance with legal requirements, and confirming that principles like data minimisation are upheld. For specific details, see the privacy impact assessments for learning technologies page.
Who has access to your learning analytics data?
Data access and minimisation
Following the principle of data minimisation, access to learning analytics data is restricted to a 'need to know' basis. Where practical, data is anonymised or presented using pseudonyms to protect student privacy.
Teaching staff access
Teaching staff responsible for individual subjects have access to subject-level learning analytics data. This enables them to understand student engagement, gain assessment insights, and enhance their teaching within that subject.
Academic and support staff access
Appropriate teaching and learning staff, along with support staff in schools and faculties, have access to learning analytics for subjects within their area. They also have access to learning analytics across multiple subjects to support broader curriculum and student experience improvements.
Central student support staff access
Central staff have access to learning analytics across all subjects. This access enables them to identify and support students who may require additional assistance.
Teaching and Learning Innovation access
Teaching and Learning Innovation supports the centrally supported learning technologies and as such has access to learning analytics within these systems needed to support the technologies and provide expert advice on innovation in teaching and learning.
University-wide reporting
Anonymised University-wide learning analytics are provided to Chancellery and other teaching and learning staff to inform curriculum development and enhance the overall student experience.
Your rights
As a student, you have the right to request access to personal information we hold about you under the Victorian Freedom of Information Act 1982 (FOI Act). You can submit a freedom of information request through the University's freedom of information process.
If you have concerns about how your learning analytics data is being used, contact the University's Privacy and Data Protection Officer.
How we manage your learning analytics data
Teaching and Learning Innovation and the University of Melbourne are committed to managing learning analytics data responsibly, adhering to established learning analytics principles to benefit you as a student and your learning outcomes, whilst avoiding bias and enhancing teaching practice. We maintain the highest standards for managing student learning analytics data.
Learning analytics principles
The table below outlines how Teaching and Learning Innovation meets each key learning analytics principle.
| Principle | How we meet this principle |
|---|---|
| Ensuring consent | Students consent to learning analytics data collection when they enrol at the University and access the LMS and University IT systems. The Victorian Privacy and Data Protection Act 2014 requires that any secondary use of this data, including research publications, must have explicit consent separate from the initial consent already given. |
| To the benefit of students and their learning outcomes, avoiding bias, (Non-maleficence and beneficence) | Teaching and Learning Innovation is committed to ensuring that learning analytics data benefits all students equitably. When reviewing available analytics in our learning technologies and generating learning analytics reports, we verify that the analytics are unbiased, genuinely beneficial to students, and do not unfairly treat any student. |
| For the enhancement of teaching design and practice | Similarly, when reviewing available analytics in our learning technologies and generating learning analytics reports Teaching and Learning Innovation is committed to providing insights that enhance teaching design and practice. |
| Transparent and ethical use of data | Students are informed about LMS data collection and its purpose through the University of Melbourne LMS privacy collection notice, the End of subject survey - privacy collection notice, and other notices (see links below) |
| Ensuring anonymity where ever practical | In accordance with the University Privacy Policy (MPF1104), student data is anonymised wherever practical in learning analytics reports and dashboards, with pseudonyms used and identity revealed only when necessary. |
| Ensuring appropriate access controls | Privacy Impact Assessment (PIA) processes ensure appropriate access controls across all learning technology systems. Teaching staff can access only subject-level learning analytics for their subjects; faculty and school staff can review cross-subject learning analytics relevant to their areas. |
| Automated decision-making and student profiling | As per the privacy policy, the PIA process ensures any automation in tools respects individuals’ privacy, is transparent, and upholds principles of fairness and accountability. |
| Best practice data management principles applied | Teaching and Learning Innovation applies best practice principles adhering to University polices for secure handling, access controls, retention, disposal, and audit expectations, documented procedures in Standard Operating Procedures. The University Records Retention and Disposal Authority reviews and sets the data retention and disposal requirements of learning analytics. Retention varies depending on the purpose of the particular data. Security and storage requirements are assessed to ensure compliance with the Victorian educational data storage requirements. |
| Community expectations | When managing and provisioning learning analytics services, Teaching and Learning Innovation consults and responds to community expectations expressed through University of Melbourne Student Union (UMSU) and University of Melbourne Graduate Student Association (GSA) and other student data consultation queries. |
| Complying with University polices and legislative requirements | Teaching and Learning Innovation operates within all applicable University policies and ensures compliance with applicable domestic and international privacy and data protection laws, including: |