🎓 EdTechOn Time📋 Fixed Price

EduTech Learning Analytics Platform — UK Multi-Academy Trust

UK6 min readUpdated June 2025
Region
UK
Contract
Fixed Price
Tech Stack
8 Technologies
IP
100% transferred

Project Overview

A UK Multi-Academy Trust (MAT) with 18 schools and 9,400 pupils needed a learning analytics platform to aggreg...

Technology Stack

Next.jsNode.js/FastifyPostgreSQLSIMS APIArbor REST APIBromcom REST APIPDF generation (WeasyPrint)AWS eu-west-2

Compliance & Standards

ICO AADC (Children's Code)UK GDPR Article 9 (SEN special category)KCSIECyber EssentialsDfE data standards
Step 01

The Challenge

A UK Multi-Academy Trust (MAT) with 18 schools and 9,400 pupils needed a learning analytics platform to aggregate attainment data across all schools, identify pupils at risk of underachievement, and provide trust-level performance insights for the Executive Headteacher and trustees. The platform needed to integrate with 3 MIS systems (SIMS in 12 schools, Arbor in 4 schools, Bromcom in 2 schools). ICO Children's Code (AADC), UK GDPR Article 9 (special educational needs data is special category), and KCSIE safeguarding data protocols were mandatory. Budget: £90,000.

Step 02

Our Approach

SIMS API via Capita Developer Programme

pupil demographics, attainment grades, attendance.

Arbor REST API

attendance, behaviour incidents, assessment marks.

Bromcom REST API

attainment, attendance, pupil premium flags.

Data normalisation

  • all three MIS systems use different grade scales and subject codes — ClickMasters built a normalisation layer mapping all to a common format.
  • At-

Risk Pupil Identification

  • Rule-based identification model (not ML — trustees wanted transparent, auditable rules that teachers could explain to parents): Pupil flagged as at-risk if ≥2 of: attendance below 90%, attainment below expected standard in 2+ core subjects, 3+ behaviour incidents in rolling 6-week window, FSM (Free School Meals) eligible with attainment gap above trust average.
  • Model reviewed annually by curriculum leads.

KCSIE

safeguarding data (referrals, child protection case notes) not included in learning analytics — accessible only via separate, DSL-gated KCSIE module.

ICO AADC

privacy by default, data minimisation (only attainment/attendance/behaviour aggregated — not biometric, health, or special needs detail).

UK GDPR Article 9

SEN data flagged but not detailed — SEN flag used for disaggregation, individual SEN records in MIS only.

Executive Headteacher dashboard

trust-wide attainment vs national benchmarks (DfE published data), pupil premium gap analysis, attendance trends, school comparison (without naming poorly-performing schools on shared screens — configurable privacy setting).

Trustee reporting pack

automated monthly PDF with key metrics for board pack.

Step 03

The Results

Platform live at 14 weeks, £84,000 — under budget.

ICO AADC: zero adverse findings.

KCSIE compliance: DSL leads across all 18 schools confirmed appropriate safeguarding data separation.

At-risk identification: 423 pupils identified in first term — interventions deployed for 89%.

Pupil premium gap: reduced from 18.3 to 15.7 months (attainment gap measure) across trust in first academic year.

Ofsted inspection at 4 schools post-launch: learning analytics cited as strength in all 4.

Client Testimonial
The Ofsted inspection was four weeks after we launched. The inspector asked how we identified at-risk pupils so quickly — the learning analytics dashboard was on screen during the inspection. All four inspections cited it as a strength. The KCSIE data separation was reviewed by our DSL network before launch — they were satisfied." — Executive Headteacher, UK Multi-Academy Trust (name withheld)
ClickMasters Case Study Team
Reviewed by James Whitmore, CTO

Project Details

Sector
EdTech
Country
UK
Status
On Time
Contract
Fixed Price
Tech Stack
8 Technologies
Reading Time
6 min
IP Ownership
100% transferred
Last Updated
June 2025
Written By
ClickMasters Case Study Team
Reviewed By
James Whitmore, CTO

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