AI Family Tutor
AI Family Tutor
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Description
Your personal AI family tutor and smart question bank generator. Simply upload a textbook chapter or a photo of missed questions, and it will instantly “translate” the material into engaging stories or analogies that elementary school students can understand. It also automatically creates targeted practice variations, helping children master difficult concepts through laughter and truly understand not only what happens, but why.
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WebpageElementary Math Game Maker
Built for elementary math teachers and parents! No coding required—select a topic to instantly generate a ready-to-use interactive practice game. Replace dull paper worksheets with engaging practice that children enjoy and want to complete, while saving hours of lesson planning and question-finding time. Generated games can be used directly on Seewo whiteboards or shared on WeChat Moments. Questions and difficulty are customizable, and the built-in question bank covers topics across all elementary grade levels in the People's Education Press, Beijing Normal University Press, and Jiangsu Education Press curricula. Ready to use out of the box.
Primary Science Quiz Game Generator
Designed for primary school science teachers and parents! No coding required. Just select the knowledge point and generate an interactive practice mini-game with one click. Solves the pain points of scattered science knowledge, children forgetting and losing interest, and difficulty finding supporting interactive exercises for lesson preparation. Saves hours of organizing test points and creating interactive materials. Generated games can be directly used in Seewo whiteboard classrooms and shared on social media. Supports customizing questions and difficulty. Built-in question bank covering all grade levels from the Educational Science Press, People's Education Press, and Jiangsu Education Press editions. Ready to use out of the box.
AI Textbook Quality Inspector
📚 AI Textbook Quality Inspector — Five-dimensional scan to make AI-written textbooks withstand review Textbooks written with AI assistance suffer from five common problems: hard-to-detect knowledge errors, instructional design lacking classroom feel, excessive 'correct but empty' statements, templated writing that feels robotic, and obscure language that makes students give up reading. This system performs a five-dimensional in-depth quality check chapter by chapter, examining each chapter from the perspectives of four roles: subject matter expert, instructional designer, fact-checker, and style reviewer. It outputs quantitative scores and directly replaceable modification suggestions. Five Dimensions: 📐 Knowledge Accuracy — Trace and correct concepts, models, and data one by one, with each error annotated with a source 🎯 Instructional Design — Review difficulty curve, prerequisite preparation, and chapter connections like a seasoned teacher 💎 Content Substantiveness — Expose 'correct but empty' statements, calculate real information gain per section 🤖 AI-Flavor Detection — Textbook-specific standards to distinguish normal writing from AI template patterns 📖 Readability — Paragraph rhythm, term density, assess whether students can read smoothly Highlight Features: 🔗 Cross-Chapter Consistency — Automatically generate knowledge profile, detect conceptual contradictions, inconsistent terminology, and duplicate definitions 🔄 Closed-Loop Iteration — After revision, resubmit and automatically track improvements, remaining issues, and new problems 📊 Layered Report — First see overview score + top 3 issues, then expand section-by-section analysis as needed 🎤 Sharp Commentary — No sugarcoating; if a definition is wrong, it says so bluntly, with each criticism accompanied by a revision reference Applicable to: AI-assisted undergraduate and graduate textbooks, academic monographs, and course handouts. Current version is optimized for undergraduate textbooks, but also works for graduate textbooks. Paste chapter → Get score → Make targeted revisions → Re-test until quality passes.
Information
- Version
- v2
- Last updated
- Runtime credits
- Usage-based
- Models
- Auto
