Automated Grading and Feedback System for Scalable Educational Assessments

The client experiences increasing difficulty in grading student submissions efficiently due to scaling constraints, leading to long turnaround times, high manual workload for educators, inconsistent feedback quality, and elevated operational costs. Limited internal resources hinder the ability to meet growing assessment demands, adversely affecting student experience and institutional growth. Existing solutions were insufficient or non-optimized for their specific needs, necessitating a tailored, automated assessment system that preserves human oversight, enhances feedback consistency, and ensures student privacy.

A large, innovative higher education institution seeking to streamline assessment processes and enhance student feedback efficiency through custom AI-powered solutions.

• Reduce time-to-feedback from several days to hours to improve student satisfaction.
• Assist human educators in grading tasks without replacing them, thereby streamlining workflows.
• Create a cost-effective, maintainable proof-of-concept for ongoing in-house development.
• Enable seamless integration with existing Learning Management Systems (LMS) and assessment workflows.
• Ensure strict privacy and security standards to protect student data during processing and storage.
• Design flexible, scalable architecture for future expansion and refinement.

• API-based integration with existing LMS platforms for secure data exchange.
• Secure token verification and encrypted communication protocols.
• Data ingestion modules to collect student submissions, attachments, and assignment data.
• Natural language processing (NLP) layer utilizing large language models (LLMs) to generate grading feedback aligned with predefined rubrics.
• Multi-threaded processing threads to generate varied feedback components and aggregate results.
• Containerized deployment environment (e.g., Docker) for portability and scalable deployment.
• Process mapping and user flow visualization tools for iterative design and process understanding.
• Auditable logs and reporting features for transparency and continuous improvement.
• Hand-off documentation and architecture details for future in-house development.

• Learning Management Systems (LMS) API integration for data exchange
• Secure token verification for user authentication
• Attachment processing tools within containers
• Reporting and analytics systems for feedback tracking

• System must support scalable processing with up to 10 concurrent processing threads.
• Maintain response times within hours for feedback generation.
• Ensure data security and privacy compliance (e.g., FERPA or equivalent).
• Design for maintainability and ease of handover for internal teams.
• Deployable on any cloud platform via containerization.

The project aims to significantly decrease assessment turnaround times, enabling feedback within hours and improving student satisfaction. It will streamline grading workflows, reduce manual workload for educators, and lower operational costs. The flexible, scalable system will support institutional growth, promote consistent feedback quality, and provide a foundation for ongoing in-house enhancements, ultimately enhancing the institution’s reputation for innovative, efficient education delivery.