The Intelligent Learning Connections project aims to develop an AI-powered application focused on enhancing collaborative learning experiences. The core functionality involves a collaborative learning matching system that intelligently pairs learners based on their performance metrics. This facilitates improved engagement and learning outcomes for participants.
The project requires the implementation of a robust machine learning model or matching engine. This system will analyze and interpret student performance metrics to facilitate intelligent pairing for collaborative learning.
Develop a user-friendly interface accessible to learners. This interface will serve as the platform for learners to engage with the collaborative learning matching system effortlessly.
Establish a feedback mechanism within the application. Learners will provide feedback on their collaborative experiences, contributing to the continuous improvement of the matching model. The feedback loop will be integral in refining the matching engine's effectiveness.
The necessary data for building the model can be accessed here. Please refer to the documentation within the repository for details on data usage, formatting, and any preprocessing steps required.
Link to Recommender Algorithm Api: https://synapse-ml.onrender.com
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Installation: Clone the repository to your local environment.
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Data Setup: Follow the instructions in the data documentation to acquire and preprocess the necessary datasets.
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Environment Setup: Set up the development environment as outlined in the provided documentation or requirements file.
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Model Implementation: Implement the machine learning model or matching engine using the provided data. Refer to the designated folders/files for model-related code and instructions.
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Interface Development: Develop the user-friendly interface, ensuring seamless interaction for users. Detailed guidelines for interface development can be found in the interface directory.
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Feedback Mechanism: Integrate the feedback loop functionality, allowing users to provide feedback on their collaborative learning experiences.
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Testing and Refinement: Test the application thoroughly, gathering insights from user feedback to refine the model and improve matching accuracy.
Contributions to this project are welcome! Please follow the guidelines outlined in CONTRIBUTING.md for details on how to contribute effectively.
For any questions, feedback, or issues, please reach out to [email/contact information].