Skip to content


Learning Analytics can be used to enhance learners’ engagement and performance in courses through the collection, analysis and reporting of online data. Used effectively, learning analytics can help improve student experience and enhance current learning and teaching practices.

The benefits of using Learning Analytics include -

  • Greater understanding of student engagement and activity patterns.
  • The limitation of speculation and subject interpretations through the use of data-driven data.
  • Identification of resource usage patterns i.e resources students are finding valuable.
  • Access patterns clarification (e.g. timing) for individual students, that can be useful in assessment submission.
  • Identification of trends and anomalies in assessments that can be used to improve future assessments.
  • Timely identification of students at risk.

 To find out more about how learning analytics can provide further benefit to your learning and teaching, please send your enquiry to the project team via email.

  • Principles for Using Student Information

    Universities need to have in place clear guidelines on ethical considerations surrounding such aspects as the rights and dignity of individuals and transparency of processes and practices, ensuring that legal obligations are met in relation to personal privacy, data collection and information protection.

    The University of Adelaide guidelines on ethical considerations is based on eight key principles:

    Principle 1:

    Learning analytics is a justified and ethical practice that is core to organisational principles.

    Principle 2:

    The University of Adelaide has a responsibility to all stakeholders to use and extract meaning from student data for the benefit of students where feasible.

    Principle 3:

    Learning analytics contributes to equitable and inclusive participation in education by providing data in support of quality learning and teaching, and student-centred practice.

    Principle 4:

    Students should not be wholly defined by their visible data or our interpretation of that data.

    Principle 5:

    The University (and its employees) will be transparent with regard to the collection, analysis and use of data from student and learning and teaching systems.

    Principle 6:

    Students should be engaged as active agents in the implementation of learning analytics (e.g. informed consent, personalised learning paths, interventions).

    Principle 7:

    Modelling and interventions based on analysis of data should be sound and free from bias.

    Principle 8:

    Adoption of learning analytics within the University of Adelaide requires broad acceptance of the values and benefits ( organisational culture) and the development of appropriate skills across the organization.

    Each of the above principles is linked to particular aspects of learning analytics.

    Principles 1, 2 and 3 aim to reflect key tenets that the University has a focus on the development of learning experiences specifically catering for the needs of students. At the same time, the University recognises diversity in student aspirations and needs and the use of learning analytics supports this recognition and student success.

    Principles 4 and 5 make clearer why the University has adopted learning analytics as one of many means of providing effective and targeted student support whilst recognising that students, as real and diverse individuals, rather than data or information, drive appropriate supports to enhance student success.

    Principle 6 reflects the shared responsibility of both the student and the University for student learning. The SLTA promotes students as co-creators and partners in learning, and in learning and teaching enhancement in addition to mobilising creativity and innovation in curriculum refresh and in learning, teaching   and teaching enhancement.

    The final principles relate to the need to ensure that any interpretation or manipulation of data to extract meaning is based on sound technique which is subject to expert peer review and, if necessary, through advice and mentoring by those more experienced in techniques of quantitative data analysis. The principles address this by aiming to use the most appropriate models and by ensuring that members of staff using the data or information are best placed to do so. Key elements of the SLTA include the promotion of the development of evidence-informed models of learning,  teaching and assessment, enriched through the use of digital technologies that result in a compelling, outcomes-based approach to enhancement and innovation, focused on the primary goal of student success.

  • To find out more about the Learning Analytics principles and the ethical use of student data, please contact the project team via email.
Learning Enhancement and Innovation

North Terrace Campus

Contact: LEI Contacts
Phone: +61 8 8313 3000