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--- |
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license: mit |
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task_categories: |
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- tabular-classification |
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- text-classification |
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tags: |
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- education |
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- k12 |
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- edtech |
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- digital-learning |
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- lms |
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- screen-time |
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- ai-tutoring |
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- educational-technology |
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language: |
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- en |
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size_categories: |
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- 1K<n<10K |
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--- |
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# K-12 Digital Learning Platforms Usage Dataset |
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## Dataset Description |
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This comprehensive dataset provides detailed information about digital learning platform usage, effectiveness, and trends in K-12 education. It covers Learning Management Systems (LMS), educational applications, AI tutoring systems, screen time impacts, and educational technology tools. |
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### Dataset Summary |
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- **Total Records**: 4 |
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- **Platforms Tracked**: 1 |
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- **Research Studies**: 1 |
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- **Market Data Points**: 1 |
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- **Geographic Scope**: United States and Canada |
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- **Time Period**: 2020-2025 |
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## Dataset Structure |
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### Categories |
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1. **Platform Profiles**: Detailed information about educational platforms including features, pricing, and technical specifications |
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2. **LMS Market Data**: Market share statistics, adoption rates, and competitive analysis |
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3. **Screen Time Studies**: Research on screen time usage patterns and educational impacts |
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4. **AI Tutoring Metrics**: Performance data and usage statistics for AI-powered tutoring systems |
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5. **EdTech Tools**: Rankings, effectiveness data, and user feedback for educational technology tools |
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### Data Sources |
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- LearnPlatform by Instructure reports |
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- Common Sense Media research studies |
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- NCES (National Center for Education Statistics) |
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- Academic research publications |
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- Platform vendor statistics and reports |
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- Market research organizations |
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## Usage Examples |
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### Research Applications |
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- Educational technology effectiveness studies |
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- Policy development and decision-making |
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- Academic research on digital learning trends |
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- Market analysis and competitive intelligence |
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### Practical Applications |
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- District technology planning and procurement |
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- Platform evaluation and selection |
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- Teacher training and professional development |
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- Budget planning and cost analysis |
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## Data Quality |
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### Validation |
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- Multi-source cross-validation |
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- Automated quality checks |
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- Expert review and curation |
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- Regular accuracy audits |
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### Limitations |
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- Self-reported data limitations in some studies |
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- Varying data collection methodologies across sources |
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- Geographic bias toward North American data |
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- Temporal lag in some research studies |
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## Citation |
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```bibtex |
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@dataset{k12_digital_platforms_2025, |
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title={K-12 Digital Learning Platforms Usage Dataset}, |
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author={Robworks Software}, |
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organization={https://robworks.info}, |
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year={2025}, |
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publisher={Hugging Face}, |
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url={https://huggingface.co/datasets/robworks-software/k12-digital-learning-platforms} |
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} |
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``` |
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## License |
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This dataset is released under the MIT License. All data is collected from publicly available sources and processed to ensure privacy compliance. |
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## Updates |
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Dataset is updated monthly with new research studies, market data, and platform information. |
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Last Updated: October 08, 2025 |
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