Atlas is a microservice designed to seamlessly incorporate competency models into Learning Management Systems (LMS). By leveraging cutting-edge machine learning and generative AI (GenAI/LLMs), Atlas empowers educators to create sophisticated competency models, fostering more effective teaching methods and improving student learning outcomes.
Competency-based education (CBE) is a proven method for enhancing learning, but its implementation can be complex and time-consuming. Atlas addresses this challenge by automating and simplifying the creation of high-quality competency models, including:
- Automatically generated relationships between competencies.
- Recommendations for linking competencies to relevant learning activities.
- AI-Powered Competency Models: Generate and recommend sophisticated competency models with minimal effort.
- Seamless LMS Integration: Works with Artemis and can be adapted to other LMSs.
- Open Source: Freely accessible to the community under the MIT license.
- Planned API & Micro Frontend: Future enhancements will allow for broader flexibility and easier interaction.
Detailed installation instructions can be found in the documentation.
To get started with Atlas and explore its features, refer to the user guide in the documentation.
We welcome contributions to improve Atlas! Please follow the contribution guidelines outlined in the documentation.
For issues or questions, please use the GitHub Issues section of this repository.
This project is licensed under the MIT License. See the LICENSE file for details.
Atlas is currently integrated with Artemis but is designed to adapt to other LMS platforms, making it versatile for a wide range of educational environments.