{"id":23184443,"url":"https://github.com/alphacrypto246/student-learning-style-prediction","last_synced_at":"2026-05-11T03:01:51.523Z","repository":{"id":265424290,"uuid":"895970875","full_name":"alphacrypto246/Student-Learning-Style-Prediction","owner":"alphacrypto246","description":"An interactive web application built with Streamlit that predicts a student's preferred learning style (visual, auditory, or kinesthetic) using machine learning, aiding educators in personalizing teaching strategies.","archived":false,"fork":false,"pushed_at":"2024-12-06T09:14:16.000Z","size":13,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-10T12:15:32.036Z","etag":null,"topics":["machine-learning","scikit-learn","scikitlearn-machine-learning","streamlit"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/alphacrypto246.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-11-29T09:36:49.000Z","updated_at":"2024-12-06T09:15:39.000Z","dependencies_parsed_at":"2024-11-29T10:42:05.986Z","dependency_job_id":"3782df2c-1ec5-4910-be04-7bf366d28c7b","html_url":"https://github.com/alphacrypto246/Student-Learning-Style-Prediction","commit_stats":null,"previous_names":["alphacrypto246/student-learning-style-prediction"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alphacrypto246%2FStudent-Learning-Style-Prediction","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alphacrypto246%2FStudent-Learning-Style-Prediction/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alphacrypto246%2FStudent-Learning-Style-Prediction/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alphacrypto246%2FStudent-Learning-Style-Prediction/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/alphacrypto246","download_url":"https://codeload.github.com/alphacrypto246/Student-Learning-Style-Prediction/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247284956,"owners_count":20913704,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["machine-learning","scikit-learn","scikitlearn-machine-learning","streamlit"],"created_at":"2024-12-18T09:19:20.516Z","updated_at":"2026-05-11T03:01:51.420Z","avatar_url":"https://github.com/alphacrypto246.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Student Learning Style Prediction\n\nThis project is designed to predict a student's preferred learning style based on their responses to a set of questions. The application utilizes machine learning techniques to analyze input data and classify students into categories such as visual, auditory, or kinesthetic learners.\n\n## Features\n- **User Input**: Collects responses from users via a web interface.\n- **Machine Learning Model**: Predicts learning styles based on input data.\n- **Interactive Application**: Built using a lightweight framework for ease of use.\n- **Customizable**: Easily adaptable to include additional learning styles or parameters.\n\n## Libraries Used\nThe following libraries are used in this project:\n\n- **Streamlit**: For creating the interactive web application.\n- **scikit-learn**: For building and deploying the machine learning model.\n- **pandas**: For handling input and structured data.\n- **numpy**: For numerical computations.\n\n## Requirements\nTo run the project, you need the following dependencies:\n\n```bash\nflask\nscikit-learn\npandas\nnumpy\n```\n\n## Installation\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/alphacrypto246/Student-Learning-Style-Prediction.git\n   ```\n2. Navigate to the project directory:\n   ```bash\n   cd Student-Learning-Style-Prediction\n   ```\n3. Run the application:\n   ```bash\n   streamlit run app.py\n   ```\n3. Install the required dependencies:\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n## Usage\n1. Run the application:\n   ```bash\n   python app.py\n   ```\n2. Open your web browser and navigate to:\n   ```\n   http://localhost:5000\n   ```\n3. Input the required data and receive the predicted learning style.\n\n## File Structure\n- `app.py`: The main script for running the Flask application.\n- `model.pkl`: Pre-trained machine learning model for predictions.\n- `templates/`: Directory containing HTML templates for the web interface.\n- `static/`: Directory for static files like CSS and JavaScript.\n- `README.md`: Project documentation.\n- `requirements.txt`: List of Python dependencies.\n\n## Dataset\nThe application requires a dataset of student responses and their corresponding learning styles for training and evaluation. The dataset should include:\n- Input features (e.g., questionnaire responses).\n- Target labels (e.g., visual, auditory, kinesthetic).\n\n## Results\nThe application provides accurate predictions of learning styles based on user input. It can help educators tailor their teaching strategies to suit individual student needs.\n\n## Contributing\nContributions are welcome! To contribute:\n1. Fork the repository.\n2. Create a new branch:\n   ```bash\n   git checkout -b feature-branch-name\n   ```\n3. Make your changes and commit them:\n   ```bash\n   git commit -m \"Description of changes\"\n   ```\n4. Push to your branch:\n   ```bash\n   git push origin feature-branch-name\n   ```\n5. Open a pull request.\n\n## License\nThis project is licensed under the MIT License. See the `LICENSE` file for details.\n\n## Acknowledgments\nSpecial thanks to the developers of the libraries used in this project and the open-source community for providing resources to build machine learning applications.\n\n---\n\nFeel free to raise issues or feature requests via the [Issues](https://github.com/alphacrypto246/Student-Learning-Style-Prediction/issues) tab.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falphacrypto246%2Fstudent-learning-style-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falphacrypto246%2Fstudent-learning-style-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falphacrypto246%2Fstudent-learning-style-prediction/lists"}