Educators and administrators were surrounded by data — assessments, growth metrics, and usage reports — yet struggled to translate it into actionable decisions. This project focused on designing a system that helps them understand what's happening and where to act, without requiring them to become analysts.
Educators had data. They lacked clarity — the conditions to make sense of what they were seeing and take confident next steps.
Too many metrics, with no filtering by role or context — data without direction
No way to surface the right report at the right moment in the teaching cycle
Significant cognitive overhead for non-technical users navigating raw dashboards
The core problem wasn't a visualisation problem — it was a decision support problem
I led the design of the Data Insights experience, focusing on how complex learning data could be structured and visualised to support real operational decisions — for teachers and administrators alike.
Insight hierarchy and information architecture across the full platform
Data visualisation patterns appropriate for each educator role and context
Component models for exploration, comparison, and drill-down interactions
Ensuring data systems, not just data pages — structure that supports decisions
Informing how learning science findings translated into product features
Supporting ethical use of student data through appropriate access and framing
The core challenge was designing a system that could surface performance data that matters to each user type — so they could understand and act on it, without being overwhelmed.
At a system level, the experience needed toSurface performance data in context and time — not as a raw dump of numbers
Pull focus toward patterns of concern from broad, multi-metric dashboards
Support detailed inspection when an educator needs to go deeper
Maintain appropriate access boundaries between teacher and admin views
Clear visual hierarchy to centre purpose — the most important signal first
Comparative structures to enable pattern recognition across cohorts and time
Progressive disclosure for deeper analysis without overwhelming the entry view
Distinct access dashboards and reports for different roles and decision contexts
Each data view was designed around a real education scenario — not a generic analytics pattern. Teacher views and admin views serve fundamentally different purposes.
All primary reporting was framed with context. Raw data alone doesn't support decision-making — without framing, numbers create noise rather than clarity.
The system helps users spot patterns without replacing professional judgment. We surfaced signals; we didn't tell educators what to do about them.
Where data could be misread or used unfairly, we built in friction — intentional design that slows down easy but harmful interpretations.
The system presented data in a way that made student performance and growth legible — designed to support planning and action at every level of the organisation.
Design PatternsContextual framing — every metric is shown alongside the question it helps answer
Attention-drawing visual cues that surface the signal worth acting on
Information scoped clearly by role — teachers see their class, leaders see the school
Clear language and labels — no jargon, no assumed data literacy
Educators could identify trends in learner performance without guessing — spending less time in raw exports and more time planning.
Meaningful insights surfaced without requiring specialist data knowledge, making the system accessible across varied levels of data literacy.
The system served diverse audiences from classroom teachers to school leaders, with role-appropriate views that reduced noise at every level.
Reduced time spent during planning sessions locating and interpreting relevant data — the system did the orientation work.
Feedback from educators emphasised the value of having data that is already interpreted during planning and review sessions — rather than data that still needs to be figured out.
This work reinforced how much trust matters when data flows through an organisation. Data products carry ethical weight — the way information is framed, scoped, and surfaced shapes how people act, and that responsibility is always present in the design.