A primary school in Nanjing
Empowered by AI-assisted teaching research tools, young teachers have significantly improved their instructional capabilities. Operationally, the tools eliminate the cumbersome process of frequently switching between multiple evaluation rubrics. In terms of professional competence, teachers are now asking more effective questions and better stimulating students' higher-order thinking in the classroom
The Challenge
Empowered by AI-assisted teaching research tools, young teachers have significantly improved their instructional capabilities. Operationally, the tools eliminate the cumbersome process of frequently switching between multiple evaluation rubrics. In terms of professional competence, teachers are now asking more effective questions and better stimulating students' higher-order thinking in the classroom
Our Solution
By simply deploying two standard cameras and an omnidirectional microphone in the classroom, audio and video streams can be seamlessly pushed to the AI teaching research platform. The system enables AI-powered analysis of teaching behaviors and content, generating comprehensive reports within 10 minutes for clear and instant data visualization. Furthermore, the streamed video fully supports both online and offline teaching evaluations
Results
Measurable success for our customers
Key Highlights
- 1No edge computing devices are required, resulting in extremely low hardware costs, making it ideal for large-scale deployment across the entire school
- 2It features highly customizable evaluation rubrics, capable of meeting the personalized assessment needs of various disciplines
- 3The in-depth analysis of teaching content provides data-driven insights that are particularly beneficial for the professional growth of young teachers
Related Cases
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The district education bureau oversees more than 50 primary and secondary schools. Traditionally, teaching evaluations relied heavily on manual paper-and-pen records, leading to inconsistent evaluation standards and significant barriers to cross-school collaborative research. Furthermore, the massive volume of teaching evaluation data generated each semester could not be effectively aggregated or analyzed, leaving educational decision-making without crucial data-driven support
Nanjing Medical University
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