Learning Analytics act as custodians of RMIT’s data for education, who gather, analyse and present data to enhance the learning and teaching experience.
This process drives improvements across the University by ensuring decisions are supported with the right data at the right time. It involves five core types of work:
Driving data governance policies and procedures that ensure the integrity and quality of data throughout its lifecycle and protect student confidentiality.
Administering surveys, connecting data systems and fulfilling data requests to provide a better understanding of the student journey and to highlight areas for improvement.
Using data to identify patterns, set key performance indicators and drive decision making to increase student engagement, satisfaction and support.
Applying the insights gained from data analysis to allocate resources where they will have the highest impact on the student experience.
Analysing data patterns to predict the student groups that are in the most need of support and providing targetied resources
All work undertaken by our team is framed by eight key principles, which ensure the integrity and transparency of our data analysis process.
These principles act as a reminder to engage students in the feedback cycle, so that our work can be targeted to actively improve the RMIT student experience.
The principles also form the basis of our data governance policies and procedures, which define clear strategies for data storage, management and implementation.
Lifen Sudirjo, Akshay Sharma & Pablo Munguia 2018
Graduate feedback plays an important role in determining whether institutions are producing ‘work ready’ graduates. This presentation compares data from graduate surveys conducted five-months and three-years post-graduation to gain insights into RMIT graduate satisfaction levels and employment outcomes.
Amelia Brennan, Akshay Sharma & Pablo Munguia 2018 (in press)
A common use of technology in higher education is the provision of online course materials, invoking an investigation of the ways in which students engage with online course content, and how their participation changes over time.
Sarah Taylor & Pablo Munguia 2018
Data solutions in the teaching and learning space are in need of pro-active innovations in data management, to ensure that systems for learning analytics can scale up to match the size of datasets now available.
Amelia Brennan, Christina Peace & Pablo Munguia 2018
Teaching face-to-face is still a major education mode in many universities, yet institutions are increasingly tasked with improving efficient use of teaching spaces.
Acknowledgement of Country
RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Luwaytini' by Mark Cleaver, Palawa.
Acknowledgement of Country
RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business.