Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Appearance settings

misolmaz/MicroLearnAI-Project-Summary

Open more actions menu

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
2 Commits
 
 

Repository files navigation

🎓 Highlight Project: MicroLearn AI – AI-Powered Microlearning Platform

💡 Overview

MicroLearn AI is an innovative, AI-driven microlearning platform designed to engage students through continuous, short-duration interactions. The system dynamically generates quizzes, mini-tasks, summaries, and personalized feedback based on real-time user performance.

Core Problem Solved

Unlike traditional LMS platforms, MicroLearn AI transforms the learning experience into continuous micro-tasks, significantly enhancing student motivation, knowledge retention, and learning outcomes by tailoring the pace to the individual.

⚙️ Technical Architecture & Stack

This project showcases expertise in building a modern, scalable SaaS platform integrating full-stack development with advanced AI services.

1. Core Platform Stack

Bileşen Teknoloji Fonksiyon
Backend / API ASP.NET Core ASP.NET Core 8 Web API Robust, scalable RESTful API for business logic.
Frontend React + TailwindCSS / Blazor Modern, responsive user interface.
Database SQL Server / PostgreSQL Reliable data persistence for user profiles and learning content.
Authentication ASP.NET Identity + JWT Secure user registration and session management.

2. AI & Data Layer

  • AI Engine: Utilizes the GPT-4/5 API for dynamic, real-time generation of:
    • Automated Quizzes & Summaries.
    • Personalized Feedback based on incorrect answers.
  • Analytics: Dedicated Python layer for processing learning data, generating performance analytics, and rendering visual reports (level graphs, progress reports).
  • Adaptation: Core logic includes a Student Profile and Difficulty Adaptation module to adjust content based on the learner's individual success curve and pace.

3. Key Features (MVP)

  • Adaptive Content: Personalized content delivery based on individual learning speed and success.
  • Educator Module: Tools for instructors to define courses, topics, goals, and access visual performance analytics.
  • Corporate Panel: Multi-user and license management for scalable enterprise/institutional use (SaaS structure).
  • Automatic Content Generation: Real-time quiz and summary creation via the GPT API.

🚀 Vision & Commercial Goals

The long-term goal is to transition MicroLearn AI into a licensed SaaS model for universities and corporate training sectors. This platform is also designed to collect academic data on the "impact of AI-based microlearning systems."


⚠️ IMPORTANT NOTE ON CODE ACCESS

This project is intended for commercial licensing and academic publication. Due to proprietary content and future commercialization plans, the source code is maintained in a private repository.

(https://www.linkedin.com/in/misolmaz/) – I am open to discussing the architecture, data models, and business implications of this project in a confidential setting.

About

SaaS architecture and overview of an AI-driven microlearning platform with adaptive content generation (GPT API). (Summary - No Code)

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Morty Proxy This is a proxified and sanitized view of the page, visit original site.