Smart Course Mapping Engine
Build knowledge, skills, and resource maps
Smart Course Mapping Engine
Build knowledge, skills, and resource maps
Showcase
Description
Turn course webpages, Excel spreadsheets, or textbook text into multidimensional maps and supporting deliverables for smart course development. For both undergraduate and higher vocational courses, it organizes course content into knowledge systems, knowledge-point hierarchies, learning prerequisites and follow-up relationships, and cross-unit connections. The result is a clear, traceable course knowledge map, supplemented with resource, assessment, and teaching application information. Building on the knowledge map, it also creates problem maps, competency maps, engineering project maps, and curriculum-integrated values maps. These show the relationships among knowledge, skills, competencies, project tasks, and educational goals, helping instructors review content coverage, alignment with learning objectives, and the completeness of instructional design. For non-engineering courses, the structure can also be adapted into suitable integrated practice projects. The final deliverables can include interactive HTML visualizations, Excel import sheets compatible with Chaoxing Fanya, and documentation covering development metrics, standards alignment, and quality-check results. During generation, confirmed information is distinguished from items requiring verification to avoid fabricating textbooks, references, links, or platform fields. This makes it suitable for course development, smart course applications, teaching-resource organization, and course quality review.
Related Skills
View all
Smart Course Dev II Workbench
Systematically transform a traditional course into a smart course. This Skill is designed for college instructors who have already completed some lesson plans, syllabi, or unit designs and wish to further develop the entire course into a smart course. Teachers only need to provide the course name, target students, credit hours, course content, and existing materials, and a complete smart course construction plan will be generated, including: 1. Course positioning and construction problem diagnosis; 2. Knowledge, ability, and quality objective system; 3. OBE course objective mapping; 4. Project-based course content restructuring; 5. Course knowledge graph structure; 6. Smart teaching model for pre-class, in-class, and post-class; 7. Digital teaching resource development checklist; 8. Course AI assistant design plan; 9. Formative assessment and course evaluation system; 10. Construction tasks, implementation steps, and deliverable list. Applicable to courses in liberal arts, sciences, engineering, medicine, economics, management, arts, ideological and political education, etc. for undergraduate and vocational colleges. This Skill focuses on solving the problem of 'how to systematically build an entire course' and does not handle actual teaching data analysis, student early warning, or course operation diagnosis. Related tasks are completed by the third-level Skill.
Knowledge Graph Engine
Automatically build five types of diagrams (Knowledge Graph, Mind Map, Concept Map, Flowchart/Architecture Diagram, Relation Diagram) from text, files, or topics, and output an interactive web page, static image, and visualization code all in one — a triple-threat solution built to the highest standards. Combines best practices from knowledge graph engineering and information visualization, supporting dynamic granularity control, disambiguation and deduplication, and multi-source cross-validation. Turn your words, files, or even a thought into a draggable, zoomable, searchable interactive knowledge graph in seconds, and export high-definition images and ready-to-use code with one click — this is the knowledge visualization "triple-threat" engine you've never experienced before. 🧠 What is the Knowledge Graph Engine? It's not the simple drawing tool you've seen before. It's a knowledge engineer + visualization expert hidden in your browser. Give it a textbook passage, a thesis, a PDF, or just a keyword, and it will automatically: 🔍 Extract core entities and clarify deep relationships 🧱 Build structured graph JSON (Knowledge Graph / Mind Map / Concept Map / Flowchart / Relation Diagram) 🎨 Output three top-tier forms: interactive web page + high-definition static image + Markdown/Mermaid/Graphviz code From now on, information organization doesn't rely on manual box drawing, and knowledge presentation is no longer just a static picture. ⚡ Why is it "top-tier"? 1. Fully automatic "text-to-graph" pipeline: No need to learn any modeling language or manually define nodes and connections. Just input content, and the engine automatically determines the graph type: Subject knowledge system? → Generates a semantically rich knowledge graph Reading notes deconstruction? → Generates a clear hierarchical mind map Process and decision? → Generates a flowchart/architecture diagram with branches Character relationship network? → Generates a multi-dimensional relation diagram Even if you just throw a topic word, it can independently gather information, fill in the content, and then generate the graph. 2. Triple-threat output covering all use cases: 🖱️ Interactive D3.js web page: Drag nodes, scroll to zoom, click for details, highlight related paths, keyword search... like operating a living map. Single-file HTML, no backend, can be embedded directly into any page or sent to anyone. 🖼️ High-definition static graph: Force-directed layout, color-coded categories, directly usable for thesis illustrations, PPT presentations, teaching materials — every label is sharp and readable. 📜 Visualization code: Generates both Mermaid and Graphviz source code simultaneously. Developers can directly insert into documentation, wiki, Notion, with unlimited expandability for secondary editing. 3. Ultimate user experience design: 🎨 Colors automatically mapped by entity type, hierarchy expressed intuitively by node size 🔗 Relationship labels displayed directly on curves — instantly see 'contains', 'causes', 'supports' 💡 Click any node, non-related parts auto-fade to focus on the thought path 🔄 Reset layout, search positioning, zoom and pan... all operations smooth as silk 4. Engineering wisdom balancing 'breadth' and 'depth': From entity disambiguation and deduplication to multi-source cross-validation; from hierarchical granularity control to dotted-line connections supporting cross-domain relationships — behind this are the best practices of knowledge graph engineering, not a toy but a productivity tool. 👥 Who needs it most? Teachers & Educational Content Creators: Turn entire textbook chapters into an interactive knowledge map — students click to understand concept relationships. Researchers & Students: Literature reviews no longer rely on text walls — one diagram clarifies the theoretical threads of dozens of papers. Product Managers & Enterprise Architects: System architecture, business processes, feature breakdown — instantly generate architecture diagrams, doubling communication efficiency. Readers & Lifelong Learners: Notes are no longer just outlines but explorable thought networks, letting knowledge truly 'grow' together. 🚀 Now, let your knowledge 'come alive' You give content, it gives insights. You give a topic, it gives a system. You give a requirement, it gives a complete deliverable of web pages, images, and code. This is not a feature; it's a workflow that elevates information into cognition. Let the Knowledge Graph Engine become an extension of your thinking, visualize your expertise, and reach every audience's 'aha moment.' — From today, don't 'draw' graphs, 'generate' graphs.
Smart Course Materials Expert
Transforms smart course development成果 in any discipline into “application / development / completion” materials tailored to provincial- or institution-level review, with professional infographics generated for each section. Uses the application template sections provided by the user; when no template is provided, it automatically applies a built-in six-module framework (development background and goals / features and innovation / smart resource development / smart teaching scenarios / smart assessment system / outcomes and promotion). Subject content, platform tools, and metric figures are fully parameterized; missing data is automatically marked with placeholders and never fabricated. The final deliverable combines a structured copy draft with 16:9 infographics in one integrated package, remaining discipline-agnostic and reusable across fields.
Information
- Version
- v2
- Last updated
- Runtime credits
- Usage-based
- Models
- Auto
