Can a data analytics solution change leadership behaviour in education?

Jonathan McCarthy 
IT Manager

In 2014 CIT’s IT Department commenced a programme to rollout a new data analytics platform to all Senior Management that would provide consistent, accurate and reliable access to some of our major data sets. Since then, the IT Department has grown its footprint in this space and increased the datasets provided to CIT’s leaders to aid their decision making. Our mission with this programme was to get the right information to the right people at the right time.

The initial focus of the project was in the Engineering and Science faculty, surfacing student retention data in a set of new user friendly analytics dashboards. Having developed the capability, it was subsequently rolled out to each department head, enabling them to “slice and dice” the data they needed. The service was then extended to include data for course monitoring from a quality assurance perspective. Michael Loftus, Head of Faculty of Engineering and Science – the first faculty to “go live” with the solution – is an enthusiastic champion of the programme:
“The solution is helping us provide rich information to our faculty management team in a timely, consistent and interactive manner. Ultimately, this is enabling us to understand the student experience in detail and create a platform for maximising student achievement and retention by identifying previously unseen opportunities for continuous improvement,” he said. “It will become even more important over time as it is used to integrate wider data sets and support cross process decision - making and predicting outcomes”

Abstract for Paper
As well as the obvious operational and strategic benefits this programme brings to CIT, this programme is also linked to my own PhD. My research is exploring the impact this data analytics programme has on leadership behaviour in CIT. As part of that research, in 2014 I took some measures of leadership behaviour across CIT from a student retention perspective. These measures included interviews, surveys and participant observation. The measures were very carefully crafted so that correlations to data, access to data and use of data could be understood. This gave me a very interesting baseline (pre analytics programme implementation) on what behaviours the CIT leadership exhibited. In 2015 I took a mid-point set of measures and again in 2016 I took a final set of measures. I have been able to compare the leadership behaviours and discuss the influence our new data analytics platform has had on leadership behaviour in CIT.

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