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AutoGrade
LANCERProject Description
An EdTech innovator sought an AI-driven solution to revolutionize student evaluation. Their goal was to eliminate manual bias, ensure fairness, and accelerate assessment workflows across institutions. AutoGrade, an intelligent application, was built to analyze student answer sheets while following exam-specific rules such as question limits and marking schemes, creating a transparent and reliable evaluation process.
Scope Of Work
The client sought Oodles for a centralized platform to automate exam evaluations, ensuring strict adherence to question paper instructions. The project involved designing a solution that could analyze student responses, apply marking schemes, validate attempted questions, and deliver instant results.
Our Solution
To meet the client’s requirements, AutoGrade was designed as a next-generation evaluation platform integrating React.js, Django, OpenAI, and MySQL.
Key Features Implemented:
- Smart Answer Sheet Evaluation: AI models interpret and assess responses, ensuring accuracy and content relevance.
- Rule-Adherent Assessment: Automatically checks compliance with exam guidelines, including attempt limits, negative marking, and scoring logic.
- Institution-Ready Scalability: Built to handle evaluations for small classes to large-scale university-level exams.
- Result Analytics & Reporting: Provides educators with detailed performance reports for better insights and decision-making.
- Secure Data Handling: MySQL and Django ensure data integrity, while React.js offers a seamless user interface.