Diagnosis & Improvement v2.0
Auto-generate diagnostic & improvement report
Description
Take your smart course from construction to active use and continuous improvement. This Skill is for university teachers who have already implemented course teaching and have data such as grades, assignments, evaluation rubrics, classroom interactions, or learning platform data. After uploading teaching data, the system will automatically complete: 1. Teaching data completeness check 2. Overall class learning analysis 3. Identification of weak knowledge points and skills 4. Student stratification and learning warnings 5. Stratified exercises and differentiated teaching interventions 6. Quality analysis of assignments, projects, and works 7. Analysis of course objective achievement 8. Design of teaching data visualization plans 9. Attribution of teaching problems 10. Continuous improvement plan for the next course cycle Applicable to various data types such as grade sheets, assignment scoring sheets, project evaluation rubrics, classroom interaction records, learning platform data, student work evaluations, AI conversation records, etc. This Skill does not redesign the entire course but, based on real teaching outcomes, helps teachers answer three questions: How well are students learning? Where exactly are the problems? How should teaching, practice, and improvement proceed next?
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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.
Smart Unit Design Starter v2.0
Turn a knowledge point into a smart teaching plan ready for class. This Skill is designed for college teachers who want to build smart courses but don't know where to start. Teachers only need to provide the course name, teaching topic, target students, and class hours to generate a complete, ready-to-implement unit-level smart teaching design. It helps you: 1. Restructure teaching objectives across three dimensions: knowledge, ability, and quality; 2. Design a truly actionable AI-enhanced classroom activity; 3. Form a complete teaching process covering pre-class, in-class, and post-class; 4. Generate student task sheets and multi-dimensional evaluation rubrics; 5. Clarify AI usage boundaries, teacher review points, and classroom backup plans. Suitable for courses in humanities, STEM, medicine, art and design, economics and management, ideological and political education, and other higher education subjects. After opening the Skill, follow the prompts to fill in basic course information, and a teaching plan will be generated. Teachers are not required to master complex prompts or prepare complete course materials in advance.
Course Design Assistant v7.0
💡 What can this assistant do for you? An expert with years of experience in instructional design and lesson plan writing, guiding you step by step to create professional-level instructional designs. (Offline training valued at least ¥3000 per session.) 📋 13-step standardized process, scientific and rigorous, no omissions From course information collection → learning situation analysis → pain point diagnosis → key/difficult point confirmation → objective writing (draft + refinement) → teaching model selection → AI tool integration → process design → evaluation design → board design → complete plan → multi-format delivery Each step includes quality checks to ensure no skipped steps, no omissions, and no vague content. 🎯 Automatic ABCD principle check, no more headaches in objective writing The system automatically checks each objective against the ABCD principle and tags Bloom's taxonomy levels (L1-L6). 📊 Dedicated "Advancedity, Innovation, Challenge" check, aligned with first-class course standards No more worrying about reviewers saying "insufficient challenge." The system quantifies the check for you. 🧠 Intelligent Bloom's taxonomy matching, automatically achieving higher-order thinking The system includes a Bloom's verb classification table (L1-L6) and automatically identifies: Each objective is automatically tagged with its level, ensuring the proportion of higher-order objectives meets standards. 🎨 Natural integration of curriculum-based ideological and political education, no more forced labeling The system provides 5 integration strategies: - Situational embedding: Introduce through real cases/historical stories (e.g., "China's high-speed rail control system from import to independent innovation") - Behavioral concretization: Replace abstract concepts with observable behaviors (e.g., "Identify violations in engineering accidents" rather than "Improve professional ethics") - Value conflict: Set ethical dilemmas to guide judgment (e.g., "Economic benefits vs. environmental protection") - Cultural inheritance: Introduce through traditional culture/institutional advantages (e.g., "The artisan spirit of ancient astronomical instruments") - Comprehensive literacy goals: Covering scientific literacy, engineering literacy, innovation literacy, digital literacy, values, humanistic literacy, and global perspective ⏱️ Time-driven design to ensure the teaching process is implementable Automatically calculate the total time for each segment Compare with the total time set by the user If the error exceeds ±5 minutes, automatically alert and provide adjustment suggestions No more awkward situations where "the design looks great but there isn't enough class time" 🤖 Deep integration of AI tools, supporting higher-order thinking rather than just efficiency improvement Three-tier architecture: - L1 Tool layer: Visualization, real-time feedback, virtual simulation - L2 Teaching layer: Personalized paths, layered tasks, collaborative support - L3 Innovation layer: AI as debate opponent, decision simulation, design assistance Only recommends domestic AI tools (Wenxin Yiyan, Tongyi Qianwen, Doubao, etc.), supports integration of teacher-built intelligent agents 📐 Comprehensive evaluation design, perfect objective-activity-assessment alignment - Diagnostic evaluation: Pre-class assessment - Formative evaluation: Process monitoring (classroom questioning, group discussion, lab reports) - Summative evaluation: Outcome validation (exams, project presentations) For L4-L6 higher-order objectives, automatically generate evaluation rubrics including four dimensions: "Depth of analysis, Innovation, Argument quality, Critical thinking" 🎭 Two working modes to suit different needs - Mode A (Quick output): Provide basic information → System automatically completes steps 2-11 → Outputs complete plan directly → Suitable for time-constrained users who trust AI judgment - Mode B (Step-by-step interaction): Gradually confirm each step → User can modify at any time → Suitable for fine-tuning and deep involvement Regardless of mode, 4 delivery formats are available: Detailed version, concise version, visual web page, teaching process framework diagram ⚡ Six core competitive advantages (unique features) 🔬 1. Scientific process, not based on intuition 13-step standardized process strictly executed in order, no skipping. Each step has clear output and quality check to ensure the design aligns with educational principles. 📊 2. Quantitative check of "Advancedity, Innovation, Challenge" Automatically detect advancedity (proportion of higher-order objectives ≥50%), innovation (real situations + innovative modes), and challenge (open-ended questions + interdisciplinary integration), aligned with first-class course standards. 🎯 3. Automatic ABCD principle verification Each objective must include "Condition-Behavior-Standard," with observable and measurable action verbs. The system automatically checks and tags Bloom's levels. 🧠 4. Intelligent Bloom's taxonomy matching Built-in L1-L6 verb classification table, automatically identifies objective levels, ensures higher-order thinking standards are met, no more worrying about reviewers saying "objective level is too low." ⏱️ 5. Time-driven design Automatically calculate segment durations, compare with total duration, alert if error exceeds ±5 minutes, ensuring the teaching design is implementable and within time limits. 📐 6. Perfect objective-activity-assessment alignment Constructive Alignment principle ensures consistency among "teaching objectives, teaching activities, and assessment methods." Each objective has corresponding activities and evaluations. 🎯 Applicable scenarios (covering all higher education) ✅ Teaching competitions: Teaching innovation competitions, young teacher teaching competitions, classroom teaching contests ✅ Course construction: First-class course applications, curriculum-based ideological and political demonstration courses, blended course design ✅ Daily teaching: New lesson preparation, teaching reform, teaching model innovation ✅ Teaching evaluation: Peer review, supervisory observation, teaching quality assessment ✅ Teacher development: New teacher training, teaching ability enhancement, teaching research 🚀 User experience Quick mode (Mode A): Provide course name, chapter, major, class hours → Select Mode A → System automatically completes 13-step process → Get complete teaching design in 30 minutes → Choose delivery format (detailed/concise/visual web page/framework diagram) Detailed mode (Mode B): Provide basic information → Select Mode B → Gradually confirm learning situation analysis, pain point diagnosis, key/difficult points, teaching objectives, teaching model, AI tools, teaching process, evaluation design, board design → Modify at each step → Complete high-quality teaching design in 1-2 hours Review mode: Upload existing teaching design → System evaluates step by step against all elements → Summarize three strengths and three weaknesses → Provide specific and actionable optimization suggestions → Generate a standardized and well-formatted evaluation report document
Diagnosis & Improvement v2.0
Auto-generate diagnostic & improvement report
Description
Take your smart course from construction to active use and continuous improvement. This Skill is for university teachers who have already implemented course teaching and have data such as grades, assignments, evaluation rubrics, classroom interactions, or learning platform data. After uploading teaching data, the system will automatically complete: 1. Teaching data completeness check 2. Overall class learning analysis 3. Identification of weak knowledge points and skills 4. Student stratification and learning warnings 5. Stratified exercises and differentiated teaching interventions 6. Quality analysis of assignments, projects, and works 7. Analysis of course objective achievement 8. Design of teaching data visualization plans 9. Attribution of teaching problems 10. Continuous improvement plan for the next course cycle Applicable to various data types such as grade sheets, assignment scoring sheets, project evaluation rubrics, classroom interaction records, learning platform data, student work evaluations, AI conversation records, etc. This Skill does not redesign the entire course but, based on real teaching outcomes, helps teachers answer three questions: How well are students learning? Where exactly are the problems? How should teaching, practice, and improvement proceed next?
Related Skills
View allSmart 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.
Smart Unit Design Starter v2.0
Turn a knowledge point into a smart teaching plan ready for class. This Skill is designed for college teachers who want to build smart courses but don't know where to start. Teachers only need to provide the course name, teaching topic, target students, and class hours to generate a complete, ready-to-implement unit-level smart teaching design. It helps you: 1. Restructure teaching objectives across three dimensions: knowledge, ability, and quality; 2. Design a truly actionable AI-enhanced classroom activity; 3. Form a complete teaching process covering pre-class, in-class, and post-class; 4. Generate student task sheets and multi-dimensional evaluation rubrics; 5. Clarify AI usage boundaries, teacher review points, and classroom backup plans. Suitable for courses in humanities, STEM, medicine, art and design, economics and management, ideological and political education, and other higher education subjects. After opening the Skill, follow the prompts to fill in basic course information, and a teaching plan will be generated. Teachers are not required to master complex prompts or prepare complete course materials in advance.
Course Design Assistant v7.0
💡 What can this assistant do for you? An expert with years of experience in instructional design and lesson plan writing, guiding you step by step to create professional-level instructional designs. (Offline training valued at least ¥3000 per session.) 📋 13-step standardized process, scientific and rigorous, no omissions From course information collection → learning situation analysis → pain point diagnosis → key/difficult point confirmation → objective writing (draft + refinement) → teaching model selection → AI tool integration → process design → evaluation design → board design → complete plan → multi-format delivery Each step includes quality checks to ensure no skipped steps, no omissions, and no vague content. 🎯 Automatic ABCD principle check, no more headaches in objective writing The system automatically checks each objective against the ABCD principle and tags Bloom's taxonomy levels (L1-L6). 📊 Dedicated "Advancedity, Innovation, Challenge" check, aligned with first-class course standards No more worrying about reviewers saying "insufficient challenge." The system quantifies the check for you. 🧠 Intelligent Bloom's taxonomy matching, automatically achieving higher-order thinking The system includes a Bloom's verb classification table (L1-L6) and automatically identifies: Each objective is automatically tagged with its level, ensuring the proportion of higher-order objectives meets standards. 🎨 Natural integration of curriculum-based ideological and political education, no more forced labeling The system provides 5 integration strategies: - Situational embedding: Introduce through real cases/historical stories (e.g., "China's high-speed rail control system from import to independent innovation") - Behavioral concretization: Replace abstract concepts with observable behaviors (e.g., "Identify violations in engineering accidents" rather than "Improve professional ethics") - Value conflict: Set ethical dilemmas to guide judgment (e.g., "Economic benefits vs. environmental protection") - Cultural inheritance: Introduce through traditional culture/institutional advantages (e.g., "The artisan spirit of ancient astronomical instruments") - Comprehensive literacy goals: Covering scientific literacy, engineering literacy, innovation literacy, digital literacy, values, humanistic literacy, and global perspective ⏱️ Time-driven design to ensure the teaching process is implementable Automatically calculate the total time for each segment Compare with the total time set by the user If the error exceeds ±5 minutes, automatically alert and provide adjustment suggestions No more awkward situations where "the design looks great but there isn't enough class time" 🤖 Deep integration of AI tools, supporting higher-order thinking rather than just efficiency improvement Three-tier architecture: - L1 Tool layer: Visualization, real-time feedback, virtual simulation - L2 Teaching layer: Personalized paths, layered tasks, collaborative support - L3 Innovation layer: AI as debate opponent, decision simulation, design assistance Only recommends domestic AI tools (Wenxin Yiyan, Tongyi Qianwen, Doubao, etc.), supports integration of teacher-built intelligent agents 📐 Comprehensive evaluation design, perfect objective-activity-assessment alignment - Diagnostic evaluation: Pre-class assessment - Formative evaluation: Process monitoring (classroom questioning, group discussion, lab reports) - Summative evaluation: Outcome validation (exams, project presentations) For L4-L6 higher-order objectives, automatically generate evaluation rubrics including four dimensions: "Depth of analysis, Innovation, Argument quality, Critical thinking" 🎭 Two working modes to suit different needs - Mode A (Quick output): Provide basic information → System automatically completes steps 2-11 → Outputs complete plan directly → Suitable for time-constrained users who trust AI judgment - Mode B (Step-by-step interaction): Gradually confirm each step → User can modify at any time → Suitable for fine-tuning and deep involvement Regardless of mode, 4 delivery formats are available: Detailed version, concise version, visual web page, teaching process framework diagram ⚡ Six core competitive advantages (unique features) 🔬 1. Scientific process, not based on intuition 13-step standardized process strictly executed in order, no skipping. Each step has clear output and quality check to ensure the design aligns with educational principles. 📊 2. Quantitative check of "Advancedity, Innovation, Challenge" Automatically detect advancedity (proportion of higher-order objectives ≥50%), innovation (real situations + innovative modes), and challenge (open-ended questions + interdisciplinary integration), aligned with first-class course standards. 🎯 3. Automatic ABCD principle verification Each objective must include "Condition-Behavior-Standard," with observable and measurable action verbs. The system automatically checks and tags Bloom's levels. 🧠 4. Intelligent Bloom's taxonomy matching Built-in L1-L6 verb classification table, automatically identifies objective levels, ensures higher-order thinking standards are met, no more worrying about reviewers saying "objective level is too low." ⏱️ 5. Time-driven design Automatically calculate segment durations, compare with total duration, alert if error exceeds ±5 minutes, ensuring the teaching design is implementable and within time limits. 📐 6. Perfect objective-activity-assessment alignment Constructive Alignment principle ensures consistency among "teaching objectives, teaching activities, and assessment methods." Each objective has corresponding activities and evaluations. 🎯 Applicable scenarios (covering all higher education) ✅ Teaching competitions: Teaching innovation competitions, young teacher teaching competitions, classroom teaching contests ✅ Course construction: First-class course applications, curriculum-based ideological and political demonstration courses, blended course design ✅ Daily teaching: New lesson preparation, teaching reform, teaching model innovation ✅ Teaching evaluation: Peer review, supervisory observation, teaching quality assessment ✅ Teacher development: New teacher training, teaching ability enhancement, teaching research 🚀 User experience Quick mode (Mode A): Provide course name, chapter, major, class hours → Select Mode A → System automatically completes 13-step process → Get complete teaching design in 30 minutes → Choose delivery format (detailed/concise/visual web page/framework diagram) Detailed mode (Mode B): Provide basic information → Select Mode B → Gradually confirm learning situation analysis, pain point diagnosis, key/difficult points, teaching objectives, teaching model, AI tools, teaching process, evaluation design, board design → Modify at each step → Complete high-quality teaching design in 1-2 hours Review mode: Upload existing teaching design → System evaluates step by step against all elements → Summarize three strengths and three weaknesses → Provide specific and actionable optimization suggestions → Generate a standardized and well-formatted evaluation report document
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