LOMCT is an e-learning tagging system designed to improve the discoverability and searchability of learning objects within the Inokufu project by associating them with relevant keywords, descriptions, reviews, and other key metadata.
Technologies Node.js, Pnpm, TypeScript, React, Shadcn/UI, Tailwind, Google Extension API, AWS EC2
Challenge The main challenge was to simplify the navigation within Learning Object repositories, helping users easily find high-quality and relevant resources. Many users struggle due to a lack of adequate metadata, inconsistent tagging, and the absence of reliable quality assessments, making it difficult to locate materials that meet their specific needs.
Key Functional Features
Tagging Module: Enables users to apply relevant keywords, categories, and attributes (e.g., difficulty level, prerequisites) to content. Feedback and Rating System: Provides users with the ability to offer both qualitative and quantitative reviews to ensure quality control. AI-Powered Moderation: Leverages AI algorithms to verify content accuracy and prevent misuse of the platform. System Integration: Develops APIs to integrate seamlessly with existing Learning Management Systems (LMS) or standalone repositories. Business Value The Learning Object system is now fully functional, intuitive, and well-received by users. Customer experience and satisfaction have significantly improved. This enhancement has enabled the system to compete more effectively with other industry players in terms of quality.
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