Project Overview: Edtech Insiders has launched an expanded generative AI map and database that categorizes over 250 AI-enabled educational tools into distinct use case categories.
- The project builds upon an earlier mapping initiative created by education technology veterans Laurence Holt and Jacob Klein in 2023
- The map organizes tools into six main categories: instructional materials, assessment and feedback, teacher practice support, teacher professional learning, student support, and social tools
- Only publicly available tools focused on K-12 education are included in the mapping system
Key Features and Functionality: The resource consists of three main components designed to help users understand and access AI educational tools.
- A visual map displays company logos representing tools with the largest reach in each use case category
- A comprehensive database provides detailed listings of AI-driven ed-tech tools for specific use cases
- A searchable directory offers information about the companies developing these tools
Current Landscape: The database reveals interesting patterns in the distribution of AI educational tools across different categories.
- Student support tools lead with 92 entries
- Instructional materials follow with 78 tools
- Teacher practice support includes 46 tools
- Assessment and feedback category contains 38 tools
- Teacher practice support has 10 tools
- Social purposes category remains smallest with 5 tools
Development and Evolution: The project has grown significantly from its initial conception to meet increasing demand for organized information about AI educational tools.
- The original map, posted on Medium in June 2023, gained significant traction among educators and developers
- The number of featured AI tools has more than doubled to 269 under Edtech Insiders’ management
- The team anticipates adding approximately 100 more tools in the coming months
Looking Forward: Market Gaps and Growth Potential: The mapping system not only showcases existing tools but also highlights areas where AI educational technology development lags, suggesting opportunities for future innovation in underserved categories like social tools and teacher practice support.
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