3. From your perspective, what are the emerging areas of interest in institutional research?

Whist trying to remain unbiased in my response, I feel that advanced analytics is emerging as a key area for institutional research. Data warehouses have historically been developed to provide the business intelligence that is generally required to assist in the running of the institution. However, it is now being recognised that these aggregated data sources can also be used as platforms for performing more advanced analyses, and that have the potential to inform decision making throughout all areas of the university. These applications may include improving current business practices, such as assisting in the targeting of university marketing campaigns, optimising room usage across the campus, or to assess the suitability of students for admission onto certain degree programs (beyond ATAR cut-offs). Nonetheless, through learning analytics programs, advanced analytics can also assist in the core business function of learning and teaching, such as the early identification of learning behaviours that may lead to poor outcomes, identifying students-at-risk of withdrawing or failing in their units, or inform academics of learning-resource usage-patterns. Therefore, whether it be to assist in the running of the institution, or for the actual core activity of learning and teaching, I believe advanced data analytics is not only emerging as a key area for institutional research, it is the future direction for institutional research.

4. What do you believe will be the future priorities for institutional research?

As discussed, data analytics is emerging as an important area for universities. However, as a practicing data scientist, I am acutely aware of the limitations we face in order to maximise the potential benefits advanced analytics has to offer. These limitations may be due to the lack of available relevant data, or more often, these limitations are due to current business practices. Increasingly, I am finding that my role as a data scientist involves informing university executives of the benefits that could result if suggested changes to current practices were adopted. To maximise the benefits from advanced analytics we need to be comparing like with like, which often requires a consistency in process to be adopted institution-wide. For this to occur, broad changes to business practices may well be required. These proposed changes often face resistance as they may be viewed as limiting academic freedom, be too expensive to implement, or not be appropriate for some courses and styles of teaching. As has been found in other sectors, the benefits of data analytics do not necessarily come easy, and that along the way difficult business decisions may well need to be made, often involving a leap of faith that the promised benefits will be worth some short-term upheaval. I therefore feel that the future priorities for institutional research will be to provide the analyses required to support university leadership teams to adopt the necessary changes to business practices designed to maximise the benefits advanced data analytics has to offer.