Abstract
![CDATA[It has become increasingly important to collect institutional data to measure and evaluate teaching and assessment improvements and to evidence quality assurance for both internal policy obligations and external review (TEQSA). However, how this data is presented, reported and targeted to individuals at various levels is of equal importance in ensuring that the correct decisions are made to maximise the student learning experience. The primary aim of this work was to see how best to provide analytic data on subjects and courses at the University of Wollongong to staff and committees for monitoring and quality assurance improvement. This presentation aims to explain how effective this has been and what lessons others can learn from this experience.]]
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Australian Conference on Science and Mathematics Education (23nd Annual UniServe Science Conference): 27th - 29th September 2017, Monash University: Science and Mathematics Teaching and Learning for the 21st Century |
| Publisher | UniServe Science |
| Pages | 112-112 |
| Number of pages | 1 |
| ISBN (Print) | 9780987183460 |
| Publication status | Published - 2017 |
| Event | UniServe Science Conference - Duration: 1 Jan 2017 → … |
Conference
| Conference | UniServe Science Conference |
|---|---|
| Period | 1/01/17 → … |
Keywords
- study and teaching (higher)
- big data
- science