UNSW Partners with Altis Consulting to Implement AI-Driven Student Success Initiative

Ranked among the world’s top 20 universities, the University of New South Wales (UNSW) exemplifies excellence in research, teaching and positive societal impact. With 7 faculties and over 60,000 current students, UNSW’s contribution to academic achievement and global engagement, positions them as a valuable servant of our society.

The vision

UNSW has embarked on a groundbreaking project aimed at improving student success through advanced data analytics and AI. In collaboration with Altis Consulting and leveraging Microsoft technologies, UNSW has implemented an AI-driven system designed to identify and support students at academic risk. This initiative is part of UNSW’s Data Insights for Student Learning and Support  project, which aims to connect at-risk students with support services.

UNSW faced the challenge of centralising educational data that was previously siloed across various departments. The university needed to create a robust data infrastructure to enable the development of predictive algorithms that could identify students at risk early in their academic journey. This project required a partner with deep expertise in data engineering, machine learning, and AI, as well as a strong understanding of the higher education sector.

The solution

Altis Consulting, in collaboration with Accenture, was selected to support this ambitious project, with the in-house UNSW team taking the lead. The existing relationship between Altis and UNSW, built on previous successful collaborations, was a key factor in the decision. The project began with a comprehensive re-architecture of UNSW’s data lake, centralising educational data to create a unified data environment. This provided the foundation for developing the AI and machine learning models that would drive the predictive analytics system.

Known as the Academic Success Monitor (ASM), the solution uses a predictive machine learning model trained on historical data from learning and administration systems. The model identifies potential academic risks by analysing students’ historical performance and their engagement within the digital learning environment. The ASM was built using Microsoft Azure, Azure Machine Learning Studio, Azure OpenAI Service, Power BI, Power Automate and Power Apps. The integration of Power Apps and Power BI provided academics with real-time insights into student performance, allowing them to track online engagement, monitor progress and tailor support to individual needs. Power Automate was utilised to build an automated messaging system, streamlining communications and ensuring students received timely, consistent updates about their academic progress and available support. 

Walter Tejada, who is part of the Educational Innovation team at Pro Vice-Chancellor of Education at UNSW (PVCE) and the project manager of this initiative, highlighted the importance of this collaboration, noting that the existing relationship with Altis streamlined the process. “The data engineering and power platform developments were super smooth due to our established clearances in terms of cybersecurity and the knowledge of available capabilities,” said Walter Tejada. Altis’ role was pivotal in identifying the right talent for both the back-end data engineering and front-end development aspects of the project.

The implementation

The project was implemented in two key phases:

1. Data Engineering and Centralisation: Altis Consulting conducted data engineering developments, while the project team and UNSW UPP led a detailed rearchitecture of the data lake, centralising previously siloed data. This phase focused on ensuring the data was ready for machine learning and AI applications. The project team worked closely with Altis to ensure
   that all data governance and security protocols were adhered to, laying a strong foundation for the project’s success.
2. Power Platform, AI and Machine Learning Automation: Once the data infrastructure was in place, Altis and UNSW collaborated on the automation of predictive models (ML Ops) that identified students at risk. The power of Azure and Power Apps was used to create actionable insights that can be used by university staff to support students proactively. After the rearchitecture developments were associated with Power Platform developments, Altis then enabled implementations of UX/UI designs from a front-end and automation perspective.

“Our CIDO [Chief Data and Insights Officer] and Altis helped wire custom configurations [of our Microsoft technology stack] together, which we wouldn’t have been able to do as quickly on our own.” Simon McIntyre, UNSW’s director of educational innovation.

Walter Tejada prasied Altis Consulting’s ability to support
both the data re-architecture and Power Platform developments in an effective, agile way - providing outstanding talent in a timely manner.

The outcome

Following a successful 2023 pilot, UNSW scaled the ASM in 2024 to 80 courses, reaching 17,000 students and 83 academics. The AI solution was effectively deployed across disciplines, offering a scalable model to enhance academic support and student engagement.

The ASM identified 284 students who were at risk of failing and in need of support, provided academics with updates and insights about student engagement in their class. In addition, 75% of academics stated the ASM identified potential risks much earlier than previously possible, and 49% of students who received proactive nudges from the system showed statistically significant increases in class engagement.

By centralising data and leveraging advanced analytics, UNSW is now better equipped to support its students and ensure their academic success. The success of this initiative has further strengthened the partnership between UNSW and Altis Consulting, paving the way for future collaborations. This case study highlights the critical role that Altis Consulting played in making this vision a reality and underscores the importance of strong partnerships in driving innovation in education.

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