Interactive Classroom Intelligence Cockpit
Experience the live ClassSignal engine. Switch between partner school cohorts below to inspect granular concept mastery curves, examine response-level student error patterns, and review Azure AI-generated micro-interventions.
Connected to Azure OpenAI Diagnostic Pipeline • Real-time Assessment Telemetry
Grading & diagnosis completed in 11 mins (vs 75 mins manual)
34 students assessed on Mathematics
Intervention ready for immediate classroom delivery
St. Jude STEM Academy (School Network)
Type: Multi-Academy Trust
Azure Tenant VerifiedConcept Breakdown & Sub-Topic Mastery
Granular skill benchmarks derived from response-level analysis
Negative Sign Inversion on Bracket Expansion
61.7% of students correctly distribute coefficients across brackets but drop or fail to negate the constant term when multiplying by a negative coefficient (e.g. -3(2x - 5) becomes -6x - 15 instead of -6x + 15).
Common Student Error Pattern
-3(2x - 5) = -6x - 15
Correct Mathematical Form
-3(2x - 5) = -6x + 15
Granular Diagnostic Depth
Grading reveals who. AI patterns reveal why it repeats.
Raw Marks vs Underlying Signal
Marks show who struggled. AI tells you why.
Standard school gradebooks record numbers like "12/20" or "60%". ClassSignal's Azure AI engine parses the actual student steps, grouping students by root conceptual error rather than raw score.
Live Cohort Telemetry
Pedagogical Philosophy
A reading of the pattern — empowering the educator
A Pedagogical Reading of the Pattern, Not a Rigid Verdict
Empowering the teacher's expertise with AI-assisted clarity
ClassSignal does not replace teacher judgment. Instead, it processes hundreds of responses instantly, detects recurring reasoning flaws across the class, and presents the teacher with clear diagnostic signals so they can act with speed and confidence.