Case study
IntelliLearn
Intelligent E-Learning Platform with Automated Assessment
- Client
- Independent project
- Duration
- Semester-length build
- Role
- Full-stack development
Overview
IntelliLearn is a full-stack learning management platform built around two AI microservices: automatic essay scoring and automatic quiz generation. Students enroll in courses, watch lecture videos, and take AI-generated quizzes; instructors upload course content, generate quizzes straight from lecture text, and review AI-scored essay submissions before publishing grades; admins manage accounts and monitor platform health, all inside one role-aware system.
The problem
Grading free-text essays and short answers by hand is slow, and the delay between submission and feedback undermines learning. Writing new quiz questions for every topic also eats into time instructors could spend teaching. Most learning platforms handle content delivery and objective-question grading well, but offer little for nuanced, open-ended assessment.
The solution
We built two independent AI microservices behind a standard React/Node.js LMS: a BERT-based essay scoring service that evaluates meaning, structure, and coherence against an instructor's rubric rather than just keyword matching, and a T5-based question generator that turns uploaded lecture text into a draft quiz ready for review. Both AI services run as separate Docker containers so the grading and generation workload never slows down the core platform, and can be updated independently of it.
What we built
AI essay scoring
Free-text submissions are scored against an instructor's rubric with contextual, rubric-broken-down feedback delivered in seconds instead of days.
Automated quiz generation
Instructors upload lecture text and get a draft MCQ or fill-in-the-blank quiz ready to review, edit, and publish.
Role-based dashboards
Distinct Student, Instructor, and Admin experiences, each scoped to their own courses, sections, and permissions.
Course delivery
Video lectures, PDFs, and structured modules with progress tracking and resume-from-last-position playback.
Performance analytics
Grade distributions, completion rates, and engagement metrics for instructors and admins, exportable as CSV/PDF.
Containerized microservice architecture
Frontend, backend, and both AI services run as independent Docker containers, so the grading and quiz-generation models can be updated without redeploying the rest of the platform.
Tech stack
Key outcomes
- Replaced manual essay grading with instant, rubric-based AI feedback, cutting turnaround from days to seconds
- Automated quiz generation freed instructors from writing every question by hand while keeping a human review step before publishing
- Independent AI microservices let the grading and quiz models scale and update without redeploying the core platform
- Role-scoped dashboards kept students, instructors, and admins each working with only the data relevant to them
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