Dynamic Active — AI LMS Prototype (Front-End)

Dynamic Active is a teacher-first Learning Management System (LMS) prototype that demonstrates explainable, rule-based “AI” decision support for tracking student progress, identifying at-risk learners, and recommending targeted lessons — all in a front-end only web app (no backend).

Demo Features

• Teacher Dashboard (Quick Overview)

  • Class summary cards: total students, at-risk count, average score
  • “Class Skill Signals” pills showing common weak skill areas
  • Intervention history log (nudges, bulk assignments, notes, completed lessons)
  • At-risk filtering + bulk actions (assign refresher, send nudges)

• Students View

  • Clickable roster list (left) → detailed student panel (right)
  • Progress + score indicators, weak skill, and risk status badges
  • Teacher notes (saved per student in-memory)
  • AI recommendation section with per-view AI toggle
  • “Open Lesson” workflow

• Lessons View

  • Recommended lesson based on student weak skill (rule-based)
  • Mini practice question + explainability (“Why this recommendation?”)
  • Mark lesson complete → logs intervention + returns to student view

• AI Insights

  • Class-level summary + explainable “What-If” simulation slider
  • Live status change based on score threshold (≥ 70 → On Track)

• Search Autocomplete

  • Top-right search supports starts-with matching first (e.g., type “A” → Aisha)
  • Keyboard navigation (↑ ↓ Enter) + click-to-jump to student profile

Tech Stack

• HTML5
• CSS3
• JavaScript (Vanilla JS)

How the “AI” Works (Explainable Rules)

This prototype uses transparent, rule-based logic (not ML):

• If lastScore < 60 → At Risk and recommend review of weakSkill
• If progress < 50 → Behind pace
• Otherwise → On Track
• Recommended lesson = first lesson matching weakSkill

Getting Started

1. Download or clone the repo
2. Open index.html in your browser (or use a local server)

Optional (recommended) local server

• VS Code: install Live Server extension → right-click index.html → Open with Live Server
• Or run:

  python -m http.server 5500