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.
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.
This project showcases expertise in building a modern, scalable SaaS platform integrating full-stack development with advanced AI services.
| BileΕen | Teknoloji | Fonksiyon |
|---|---|---|
| Backend / API |  ASP.NET Core 8 Web API |
Robust, scalable RESTful API for business logic. |
| Frontend | React + TailwindCSS / Blazor | Modern, responsive user interface. |
| Database |  / PostgreSQL |
Reliable data persistence for user profiles and learning content. |
| Authentication | ASP.NET Identity + JWT | Secure user registration and session management. |
- 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.
- 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.
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."
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/) β I am open to discussing the architecture, data models, and business implications of this project in a confidential setting.