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However as the university already has a strategy in

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However, as the University already has a strategy in place, SASSE is likely to remain as an inputinto the data sets.After encountering the Predictive Analytics Reporting (PAR) Framework (a division of HobsonsInc), HERI started to shift its focus from descriptive to predictive analytics (Department forEducation Innovation 2016 to 2019). Large volumes of University data were processed byHobsons and two reports were received from the PAR Framework, both indicating that coursecredits are highly predictive of progression and graduation rates. This evidence was theincentive for the implementation of the nudging campaign. According to Desouza and Smith(2016: 12), “the concept behind nudging and nudge theory centers on prompting individuals tomodify their behavior in a predictable way (usually to make wiser decisions) without coercing
77them, forbidding actions, or changing consequences”. As part of this activity, HERI researchersgained skill in working with large datasets and preparing them for data analysis and datavisualisation. They started using the Student Success Matrix (SSMx) as a tool and conducteda number of interviews with deputy deans of faculties. The SSMx is an intervention inventorysoftware tool that is used to document, measure and share student interventions with keystakeholder across the University. They continued to map interventions on the SSMx to obtaina broad perspective of the interventions at the various stages of the student life cycle.3.3.2Institutional research and HEMISThe University has had an institutional research unit for many years. One of its main functionsis to collect and audit institutional data, including student success and completion data,for institutional decision-making and for reporting annually to the Department of HigherEducation and Training, which is the entity through which public universities are subsidised.The data are high-level and aggregated and therefore of limited direct use to staff in decidingon student success initiatives at module or individual level.HERI has always had a student rather than a governance orientation. It started to collaboratewith Institutional Research and Analytics (IRA) on a cluster analysis after the first-semesterstudent success data became available (Department for Education Innovation 2010). Acluster analysis is a statistical method for finding relatively homogeneous clusters of casesbased on measured characteristics. The analysis showed which students were at risk basedon their first-semester marks. Originally, such students were referred to tutorials and thefaculties. Once a system of Faculty Student Advisors had been developed, the results couldbe communicated to them so that they could proactively contact students at risk. This typeof referral mechanism only developed after the formation of the Steering Committee forStudent Access and Success. (See Chapter 5 on Faculty Student Advisors and Chapter 7 on[email protected] for more information on advising.)IRA switched to the Higher Education Data Analyser (HEDA) software system in 2015. The newsoftware has allowed them to produce directly accessible dashboards for faculties and otherrole-players. The dashboards are not static and users can adjust parameters to focus theresults of their queries. Through Tshebi, particularly during 2018, capacity was developed inthe faculties on the optimum use of these dashboards.

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