Overview
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The University of Law is a specialist education provider with 8 campuses in the UK and 1 in Hong Kong.
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They use the StREAM student engagement analytics platform to improve learning, teaching, and student support.
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This case study explores how ULaw leverages student engagement data to drive strategic changes and enhance the student experience.
The challenge
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The University of Law needed to adapt and refine their approach to effectively support diverse student needs across multiple campuses.
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Ensuring the widespread adoption and effective use of StREAM across the institution was critical for success.
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Generating meaningful management insights from engagement data required a simple, yet effective, approach.
The outcome of this desired piece of incredibly transformational
transit programme is the student … and the tool to enable these conversations for those two key use cases – students at risk … and the academic development and enhancement activity is StREAM.
The University of Law’s approach
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The University of Law adopted StREAM to gather and analyse student engagement data in 2019.
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The data informs management decisions, supports student engagement initiatives, and improves the student journey.
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Power BI is used to transform engagement data into actionable insights for executive decision-making.
The impact
Data-drive decisions
The use of StREAM and Power BI has streamlined decision-making and enhanced the strategic focus on student support. Regular updates and easy-to-use dashboards have made data-driven insights accessible and actionable for university leaders.
Improve student support
By embedding StREAM across the institution and ensuring leadership are invested, the University of Law’s approach has provided significant insights into student support effectiveness, contributing to the university’s high teaching and employability ratings.
Better student outcomes
Engagement data has led to improved student outcomes and more targeted interventions. The University of Law’s integration of StREAM with Power BI has maximized the value of student engagement data with minimal effort.
Future developments
Future developments aim to further refine and automate data analysis to enhance student engagement and success.
