An ongoing commitment to excellence and improvement in the quality of teaching remains the stated value of every higher education institution in Australia. With increasingly sophisticated tools to extract ever more nuanced information, the actualisation of this goal should be clearer than ever before.
But is actual progress being made? Or is this a case of all sizzle and no steak?
There is an additional stage in the journey that is often lost amidst the glamour and promise of analytics tools – how do institutions actually use this data to implement change and continuous improvement in the quality of their learning and teaching?
At present the approach is highly variable across the sector, and the success often depends on the motivation, buy in and data literacy of multiple stakeholders in key positions to effectively function. Weak links in the chain will often derail the best of intentions.
Learning analytics yet to be mastered
True progress requires the institutional vision and strategy to be aligned with the practices and beliefs of academic and professional staff throughout the university. This further requires the functional embeddedness of support structures to continually reinforce the desired performance at each level, as well as the more prosaic and functional capabilities to: record, measure, analyse and present timely, actionable data when and where it’s required.
Learning analytics, though continually evolving, are hardly an emerging discipline. That no single institution can claim mastery of this process indicates clearly that this is a matter of more easily said than done. With quality of the learning and teaching experience perceived as the cornerstone of economic competitiveness, the future success of higher education is intrinsically linked with the ability to understand and continuously improve their respective qualities.
The Measuring and Improving Quality in Learning & Teaching conference, running this September in Sydney, aims to address the disconnect between data and actionable change. All the data in the world is useless if meaningful and actionable information cannot be extracted and effectively presented. Likewise, without the appropriate support structures and alignment of values, genuine implementation remains just a pipe dream.