Articles

Learning Analytics Purpose

TLDRoffon

Combining data held about students in a new way to support learning and enhancing educational processes.

The purpose of Learning Analytics at the University of Greenwich:

Quality

  • Learning Analytics can be used as a form of feedback on the efficacy of pedagogical design.
  • Academic teams can use analytics about student activity (individual or cohort) as part of course review and re-design processes as well as potentially using analytics as a form of in-course monitoring and feedback.
  • Individual staff can use Learning Analytics to reflect on the impact of their teaching.

Equity

  • Learning Analytics approaches can allow us to see more nuanced views of our highly diverse student population, challenge assumptions that we may be making, and allow supportive resource to be directed where it is most needed.

Personalised feedback

  • Learning Analytics can be used to tailor the messages and support we offer to our students, providing more personalised feedback to support student reflection and academic planning.

Coping with scale

  • As part of an enhanced staff engagement programme, Learning Analytics can help strengthen the academic relationship by doing some of the heavy lifting of identifying individuals or groups of individuals that might benefit from particular interventions or information from staff.

Student Experience

  • In addition to supporting a more personalised experience, Learning Analytics can improve progression and retention, ensure that our academic offerings align with the needs and goals of students, and support satisfaction and wellbeing.
  • Learning Analytics can also be used to promote critical reflection skills and enable our students to take responsibility for their own learning.

Skills

  • Interactions with Learning Analytics as part of the university learning experience can help our students build 'digital savviness' and prompt more critical reflection on how data about them is being used more generally, what consent might actually mean and how algorithms work across datasets to define and profile individuals.
  • Learning Analytics approaches can also be used to promote the development of key employability skills.
  • Supporting staff to develop skills in working with Learning Analytics applications is also an investment in institutional capacity and leadership.

Efficiency

  • Learning Analytics can be used to evaluate and demonstrate institutional efficiency through:
    • Measuring the impact of initiatives and validating that benefits are being realised.
    • Demonstrating that publically-funded resource is being deployed in support of the best outcomes of all students.