An AI practical training guidebook customization generation method based on skill map analysis

By using large language models and skills graph analysis, multimodal teaching content is identified and generated, solving the problems of fragmented content and low standardization in traditional training manual writing. This enables the efficient and customized generation of training manuals to meet the actual needs of enterprises.

CN122434698APending Publication Date: 2026-07-21ZHONGJIAO YUNZHI DIGITAL TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
ZHONGJIAO YUNZHI DIGITAL TECH CO LTD
Filing Date
2026-04-29
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Traditional training manuals suffer from fragmented content and low standardization, making it difficult to match with real-world enterprise project processes. Furthermore, existing AI-generated training manuals cannot accurately identify and break down key elements, resulting in inconsistent logic and a lack of effective connection between the generated manuals and job skill maps, thus failing to meet diverse learning needs.

Method used

Using a large language model, we perform deep semantic understanding to identify key elements and associate them with pre-set job skill maps. Based on real enterprise workflows and project lifecycles, we orchestrate task chains to generate multimodal teaching content. Finally, we package the content according to a standardized digital textbook template to ensure that the teaching content is consistent with job skill requirements.

Benefits of technology

It enables the customized, standardized, and systematic generation of practical training manuals, improves generation efficiency, ensures that teaching content is consistent with job skill requirements, meets diverse learning needs, and reduces the threshold and cycle of course development.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses an AI practical training guidance book customization generation method based on skill graph analysis, which can convert unstructured original practical training materials into structured and project-based intelligent digital practical training guidance books. First, a large language model is used to deeply understand the original practical training materials and disassemble key elements, associate the key elements and their contents with the pre-set post skill graph, and complete the precise connection of the elements according to the hierarchical relationship. Then, based on the enterprise real work flow and project life cycle, the task chain is arranged, and the course outline is generated. Then, the multi-modal teaching content is intelligently matched or generated and filled into each node. Finally, the practical training guidance book is packaged and verified and published. It can be widely applied to the fields of vocational education and enterprise training, and provides strong support for cultivating professional talents meeting the needs of enterprises, and solves the problems of fragmented content, low standardization and difficulty in matching the actual needs of enterprises in traditional practical training guidance book compilation.
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