Learning data and analytics

About learning data

Learning data refers to the traces that learners leave behind when using educational technology across the learning and teaching landscape at Charles Sturt.

The use of data has a well-established place in educational methodology and learning design. What is relatively new is the large amount of learning data available as students engage in their studies using the learning management system, Interact2, and the variety of other education technology platforms at the University.

Learning data offers actionable information to support learning and teaching in different ways:

• Teaching staff: use learning data to provide feedback to students on their learning activity and progress and to make informed decisions regarding learning and teaching interactions
• Design and development staff: use learning data as a key component to measure and gain insight into the impact and redesign of learning designs within the course and subject structures
• Faculty educational leadership: use learning data to provide alerts and reports that enable and inform appropriate management interventions and professional development strategies.

Educational technology systems automatically collect and store all user data, which can then be reported on:

• for an individualised user in a specific teaching period and subject
• at an aggregated level examining large subsets of students or the entire student body population.

Incorporating data into learning and teaching practices and design and development processes is the basis of an evidence-informed approach to support, improve and innovate the student learning experience at Charles Sturt.

Using learning data

Learning data reporting mostly measures content activity rather than conclusive learning behaviour. Data may help you determine, for instance, which teaching practices are working best, but maybe not why.

The best place to start is with the pedagogy rather than the data. Have a question, or begin with an issue you’d like to resolve. Then, analytics approaches can be used to gain insight from learning data to improve learning and teaching.

Ethical and responsible use of data

In the use of student data, it’s important to recognise the role we have in the protection of student privacy. Our data practices are governed by the Charles Sturt Learning Analytics Code of Practice, and we comply with the University's Privacy Management Plan and data security policies. As with student grades and other sensitive data, you should use learning data and analytics on a ‘need to know’ basis.

Learning data for teaching staff

Several data analytics tools are available in the form of reports and dashboards that provide you with actionable information to help improve learning and teaching.

Access and use student data

Utilising data for decision-making is a crucial step in designing and delivering subjects. Brightspace allows you to access and use student data to create a student-centred and adaptive experience.

Access and use data in teaching

Use intelligent agents to automate communication

The intelligent agent's tool lets you set up automated processes that monitor student activity in your Brightspace subject based on your chosen criteria. These agents can send customized emails to students, teachers, or other relevant individuals.

This tool can help provide timely support to students, improving their chances of success. Tracking logins, submissions, discussion participation, and quiz scores can identify students needing extra help or intervention.

Brightspace intelligent agents