Understanding the educational technology behind modern assignment management
ShikshaSetu emerged from a simple observation: professors spend countless hours creating assignments and even more time grading them. This platform was built to solve that problem using artificial intelligence, while maintaining the educational quality that matters most to educators.
Rather than being another complex learning management system, ShikshaSetu focuses on one thing and does it exceptionally well - assignment creation and evaluation. Think of it as having a teaching assistant that never gets tired, never makes grading mistakes, and can generate thoughtful questions on any topic you specify.
The architecture separates what users interact with from the complex processing that happens behind the scenes. This means professors get a clean, intuitive interface while the system handles the technical complexity of AI integration and data management.
Simply enter your email - the system recognizes professors automatically and gives you full access to all features.
Add student email addresses to grant them access. You control who can see and take your assignments.
Choose your topic, set difficulty level, specify question types. The AI does the heavy lifting of question generation.
Preview the generated questions, make any adjustments, then publish for students to access.
The system grades everything automatically and provides detailed analytics. Release results when ready.
Use your student email to login. Only students added by professors can access the system.
See all available assignments from your professors with clear information about topics and requirements.
Answer multiple choice questions and write responses to open-ended questions in a user-friendly interface.
Submit your completed assignment with one click. The system prevents multiple submissions to ensure fairness.
Once professors release grades, see your scores, detailed feedback, and learn from any mistakes.
AI creates questions that match the rigor of top universities, with proper validation and fallback options
Instant grading for multiple choice, intelligent evaluation for written responses with detailed feedback
Professors manage student access, ensuring only enrolled students can participate in assignments
Comprehensive grade reports, analytics export, and progress monitoring for better educational outcomes
The technology choices prioritize reliability and ease of deployment. Python and Streamlit provide a robust foundation, while OpenAI integration brings intelligence to question generation and evaluation. The JSON-based storage system ensures portability and simplicity for initial deployments.
| Function | What It Does | Why It Matters |
|---|---|---|
generate_mcq_with_ai() |
Creates multiple choice questions using AI | Ensures consistent quality and saves preparation time |
evaluate_answer_with_ai() |
Grades responses and provides feedback | Fair evaluation with personalized learning guidance |
authenticate_user() |
Manages login and permissions | Protects academic integrity and student privacy |
publish_assignment() |
Makes assignments available to students | Controls timing and access to coursework |
Moving from JSON files to a proper database system will support larger numbers of concurrent users and provide better data management capabilities for institutional deployment.
Learning pattern analysis could help identify students who need additional support and provide insights into the effectiveness of different question types and difficulty levels.
Adding support for mathematical notation, images, and interactive elements would expand the types of subjects and assessment methods the system can handle effectively.
Integration with existing learning management systems and student information systems would streamline adoption and reduce administrative overhead for educational institutions.