Risk & Compliance

Advanced Analytics

Monash is a modern, global, research-oriented university, delivering education and research excellence in Australia and across the Indo-Pacific. It has a vibrant and diverse community of 86,000 students & 17,000 staff across three international teaching locations & six distributed campuses. Throughout Monash’s 60-year history, positive changes stemming from their alumni can be found in fields of climate science, geo-political security and economics.

Monash had an online electronic invigilated assessments system known as e-Assessments, where students studying remotely can do their assessments in a safe and secure environment with exam invigilators monitoring the service and viewing the student via their laptop cameras.

The e-Assessments system is a separate instance of Monash’s LMS used for teaching. It collects and store many data points from the assessments, including student actions while attempting online assessments. This system was supported by Monash’s central IT team at Monash University who believed that the system could be a valuable source of data trends and patterns for examining student behaviour and exam policy decision making. The team was looking to support live invigilation for tens of thousands of remote and open book e-Exams annually. Revenite were asked to help Monash achieve their goals for scaling up live invigilation and better policy decisions for exam planning and execution. They partnered with Revenite to do discovery of their current state platform and data points and advise next steps to support a wider vision of “Academic integrity” and “Risk modelling” at Monash University.

Revenite team performed discovery by having workshops with various stakeholders at Monash to understand the current state of e-Assessments and eVigilation data sets and established the scope of data analytics visualizations and dashboards.

Data profiling of entities and relationships was completed to establish data points of interests for analytics. Revenite team established a common data model in Power BI using identified entities and relationships. Summary and analytical findings about technical issues during exams and significant events such as students assigned red flags during online assessments, were visually analysed in Power BI. The Power BI visualisations presented interesting correlation analysis about student behaviour during various assessments and supervisor invigilation activities as a result of student behaviour.

Revenite team proposed a Microsoft reference architecture to support in exam and post exam analytics by integrating datasets from all source systems including e-Assessments. The discovery report, Power BI Common data model and reference architecture helped Monash in establishing a data roadmap for future data engineering work to continue ensuring Academic Integrity at Monash.

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