AI-assisted Educational Quiz Platform
A generic AI learning assistant that can generate quizzes and learning interactions from prompts or uploaded files. It uses a Socratic questioning style to guide learners, provides explanations when mistakes are made, and will evolve to support richer conversational study and historical/theoretical discussions.
Project Overview
futurEdAI is a flexible educational assistant that accepts prompts or files and turns them into interactive learning experiences. Using a Socratic approach, it asks guided questions to help users reason through material. If a learner answers incorrectly, futurEdAI explains the mistake and reinforces the concept. In future iterations the system will support ongoing dialogue about theory, history, and deeper context for technical subjects.
NOUS: Transforming Education
NOUS leverages cutting-edge AI to create personalized learning experiences that adapt to each student's needs. By combining natural language understanding with pedagogical best practices, we're transforming how knowledge is shared and acquired.
Our system analyzes learning patterns, identifies knowledge gaps, and delivers custom content that challenges students at the right level. The result? More engaged learners, better retention, and deeper understanding.
Key Features
- Socratic questioning - Guides learners with targeted questions rather than just giving answers.
- Explanations on mistake - When answers are incorrect, the system provides concise, teachable explanations.
- Prompt & file input - Accepts free-text prompts or uploaded files as sources for questions and discussion.
- Per-question results - Individual results and feedback appear inline for each question.
- Future conversational mode - Planned capability to hold interactive discussions about theory, history, and related context.
Technical Implementation
The project uses a server-side backend (Django) that connects to language model APIs to produce structured quiz content. The frontend is implemented with JavaScript and minimal frameworks to render interactive quizzes, capture answers, and show inline feedback and explanations. Files uploaded by users are temporarily forwarded to the model pipeline for analysis. Error handling is built in so the system can return informative fallbacks when content cannot be processed.
Team Credits
Ioannis Paterakis
Backend & server structure
Mihalis Karapiperakis
API design
Vaggelis Kampagiouklis
Logo Design