Features Overview

Learning intelligence,
not just
content delivery.

AdaptiveHub is an AI-assisted A-LMS built for Philippine K–12 schools. Five deeply integrated systems observe, respond to, and continuously improve every student's learning path — in real time.

Explore features → View live demo
Core Architecture

Five systems
working as one.

AdaptiveHub is not a feature list — it's a unified intelligence platform. Each system feeds the next, forming a closed loop that continuously improves every learner's path.

LMS Core
A full classroom infrastructure — lessons, quizzes, assignments, and enrollment — built as the foundation that every intelligent layer builds upon.
LessonsQuizzesAssignments
AI Adaptive Engine
Continuously evaluates student indicators — proficiency, mastery, familiarity, and risk — then adjusts difficulty, triggers remediation, or unlocks enrichment automatically.
Adaptive scoringRemediation logicPath tuning
Behavioral Analytics
Tracks not just scores, but how students learn — retry patterns, session duration, completion consistency, and engagement intensity. Behavior reveals what scores hide.
Real-timeRisk flagsTrends
Gamification
XP, streaks, badges, and class leaderboards convert daily learning habits into motivated, measurable progress — designed for real Philippine K–12 classrooms.
XPStreaksLeaderboard
Teacher Tools
Dashboards, risk indicators, and remediation controls give teachers the right insight at the right moment — augmenting judgment without replacing it.
DashboardRisk alertsIntervention
Curriculum-Grounded AI
Every AI-generated question and explanation is anchored to MATATAG competencies through AdaptiveHub's controlled curriculum layer - aligned, traceable, and classroom-ready.
MATATAGCurriculum layerTraceable outputs
Learner Modeling

Every learner
builds a living
profile.

The student profile isn't set at onboarding and forgotten. It recalibrates after every quiz, lesson, and assignment — becoming a precise, real-time representation of each learner.

01
Authentication & Enrollment
Students enter through mobile or web with role-verified access tied to their class, school, and curriculum level.
02
Profile Survey
An onboarding survey captures learning preferences, confidence levels, and subject comfort to seed the initial learner model.
03
Starting Level Classification
The system assigns an initial proficiency tier — Approaching, Developing, or High — that immediately shapes content difficulty and pacing.
04
Learning Hub Activation
Students access their personalized dashboard — classes, lessons, assignments, leaderboard, streaks, and calendar — all in one adaptive workspace.
05
Profile Update & Continuous Loop
After every interaction, the system re-evaluates indicators and updates the learner model. The profile never goes stale.
Student Profile — Live Indicators
Ana Reyes · Grade 8 · Mathematics
Proficiency
74%
Mastery
61%
Familiarity
88%
Engagement
82%
Consistency
69%
Live recalibration
Non-linear path
Mastery
61-72
Focus
82-68
Risk
Med-Low
Quiz
Word problems improved
Hint use
Temporary struggle detected
Review
Confidence recovered
AI Decision
Mastery is below proficiency — assigning targeted Word Problems review. Notify teacher if no improvement after 2 attempts.
Adaptive Intelligence Loop

From interaction
to
intervention.

AdaptiveHub's operational heartbeat transforms every student action into a learning direction decision — through observation, analysis, adaptive response, and recalibration. The loop never stops.

Try the loop live →
Stage
What happens
Interaction
Lessons, quizzes, assignments, logins
Observation
Time, attempts, hints, completion captured
Indicator Update
Proficiency, mastery, engagement recalculated
Decision
Maintain, adjust, remediate, or enrich
Outcome
Track whether intervention improved learning
Recalibration
New baseline for the next cycle
Teacher Augmentation

Human oversight
stays central.

AdaptiveHub augments educators — it doesn't replace them. The platform surfaces the right data at the right moment so teachers spend less time finding problems and more time solving them.

Class Analytics
Live class-wide proficiency maps, per-topic mastery breakdowns, completion rates, and engagement summaries — all in one glanceable dashboard.
Risk Detection
The system automatically flags students showing declining trends, repeated failures, or engagement drops — before those signals become visible in grades alone.
Remediation Control
Assign targeted review sessions, approve AI-suggested remediation content, or override the adaptive engine entirely — teacher authority is always preserved.
Institutional Insight
For coordinators and principals: class-versus-class comparisons, school-level learning gap reports, and intervention outcome tracking across the institution.
Platform Stack

Built as an
adaptive
platform stack.

AdaptiveHub runs on a production-grade architecture - Laravel backend, Flutter mobile, secure learning data services, and our Claude Opus 4.7 powered AI Adaptive Engine - designed to scale from pilot classrooms to national deployment.

Backend
Laravel 11 + PHP
Sanctum auth, queue jobs, API-first architecture
Database
MySQL 8 · pgvector
Relational data + 768-dim vector store on Supabase
Adaptive Intelligence
AI Adaptive Engine
Powered by Claude Opus 4.7 for curriculum-aware personalization, remediation logic, and learning path decisions
Mobile + Web
Flutter · GetX
Teacher and student native apps · Blade web portals
Get started

See the adaptive
system in motion.

Walk through onboarding, live assessment, teacher support, and the full intelligence loop inside AdaptiveHub.

Request a demo → Open live demo