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docs/learning-graph/docs/learning-graph/docs/learning-graph/book-metrics.mdmkdocs.ymldocs/learning-graph/chapter-metrics.mddocs/course-description.mddocs/learning-graph/book-metrics.mdmkdocs.ymldocs/learning-graph/chapter-metrics.mddocs/course-description.mdmkdocs.ymlsite_namesite_urlsite_descriptionrepo_urldocs/course-description.mdsite_name: 'Geometry for High School Students'
site_url: 'https://username.github.io/geometry-course/'
site_description: 'An interactive geometry textbook with MicroSims and quizzes'mkdocs.ymlsite_namesite_urlsite_descriptionrepo_urldocs/course-description.mdsite_name: 'Geometry for High School Students'
site_url: 'https://username.github.io/geometry-course/'
site_description: 'An interactive geometry textbook with MicroSims and quizzes'docs/learning-graph/book-metrics.md| Metric Name | Value | Link | Notes |docs/learning-graph/book-metrics.md| Metric Name | Value | Link | Notes |This intelligent textbook on [TOPIC] is designed for [AUDIENCE]. Built using MkDocs Material and AI-assisted content generation, it incorporates learning graphs, concept dependencies, and interactive MicroSims to make [TOPIC] accessible and engaging.📊 By the numbers:
• [X] chapters covering [TOPIC AREAS]
• [Y] concepts in the learning graph
• [Z] interactive MicroSims (p5.js simulations)
• [Q] quiz questions for self-assessment
• [G] glossary terms with ISO 11179-compliant definitions
• [W] total words (~[P] equivalent printed pages)Generated using Claude AI skills and the intelligent textbook framework, this open-source project demonstrates how AI can augment educational content creation while maintaining quality and pedagogical rigor.Explore the full textbook here: [SITE_URL]#AI#ArtificialIntelligence#GenAI#GenerativeAI#Education#EdTech#EducationalTechnology#OpenEducation#OER#ELearning#OnlineLearning#Textbook#InteractiveTextbook#MicroSims#Simulations#Visualizations#DataViz#Diagrams#Infographics#Quizzes#Assessment#MkDocs#MaterialDesign#p5js#JavaScript#Python#ClaudeAI#AnthropicClaude#Mathematics#Geometry#Calculus#Algebra#Physics#Chemistry#Biology#Programming#ComputerScience#DataScience#History#WorldHistory#AmericanHistory#LMS#LearningManagementSystem#CurriculumDesign#InstructionalDesign#STEM#STEMeducation#HigherEd#K12Education这本关于[主题]的智能教材专为[受众群体]设计。基于MkDocs Material与AI辅助内容生成技术构建,融入了学习图谱、概念依赖关系和交互式MicroSims,让[主题]学习更易懂、更具吸引力。📊 数据概览:
• [X] 个章节,覆盖[主题领域]
• [Y] 个学习图谱中的概念
• [Z] 个交互式MicroSims(p5.js模拟)
• [Q] 道自测测验题目
• [G] 个符合ISO 11179标准定义的术语表条目
• [W] 总字数(约[P]等效印刷页数)本项目由Claude AI技能与智能教材框架生成,展示了AI如何在保持内容质量与教学严谨性的同时,助力教育内容创作。点击探索完整教材:[站点链接]#AI#ArtificialIntelligence#GenAI#GenerativeAI#Education#EdTech#EducationalTechnology#OpenEducation#OER#ELearning#OnlineLearning#Textbook#InteractiveTextbook#MicroSims#Simulations#Visualizations#DataViz#Diagrams#Infographics#Quizzes#Assessment#MkDocs#MaterialDesign#p5js#JavaScript#Python#ClaudeAI#AnthropicClaude#Mathematics#Geometry#Calculus#Algebra#Physics#Chemistry#Biology#Programming#ComputerScience#DataScience#History#WorldHistory#AmericanHistory#LMS#LearningManagementSystem#CurriculumDesign#InstructionalDesign#STEM#STEMeducation#HigherEd#K12Education📸 Suggested visual: Screenshot of the learning graph visualization or the textbook home page📸 推荐配图:学习图谱可视化截图或教材首页截图undefinedundefinedundefinedundefined✅ LinkedIn announcement generated successfully!
Three variations provided (full, medium, concise) - choose the one that fits your style.
**Next steps:**
1. Copy your preferred version
2. Paste into LinkedIn post composer
3. Add a screenshot of your textbook (optional but recommended)
4. Review and post!
Pro tip: LinkedIn posts with images get 2x more engagement. Consider adding a screenshot of your learning graph or textbook homepage.✅ LinkedIn公告生成成功!
提供了三个版本(完整、中等、精简),请选择符合你风格的版本。
**后续步骤:**
1. 复制你偏好的版本
2. 粘贴至LinkedIn帖文编辑器
3. 可选添加教材截图(推荐)
4. 检查后发布!
小贴士:带图片的LinkedIn帖文互动量是纯文本的2倍。建议添加学习图谱或教材首页的截图。🎓 Excited to share a new open educational resource: an interactive textbook on Geometry designed for high school students!
This intelligent textbook combines AI-assisted content generation with proven educational frameworks. Built using MkDocs Material, it incorporates learning graphs showing concept dependencies, interactive MicroSims using p5.js, and comprehensive assessment tools to make geometry accessible and engaging.
📊 By the numbers:
• 13 chapters covering points, lines, angles, triangles, polygons, circles, and 3D geometry
• 200 concepts organized in a dependency graph
• 5 interactive MicroSims (p5.js simulations)
• 10 quiz questions for self-assessment
• 22 glossary terms with precise definitions
• 225,000+ words (~900 equivalent printed pages)
Generated using Claude AI skills and the intelligent textbook framework, this open-source project demonstrates how AI can augment educational content creation while maintaining pedagogical quality and rigor.
All content follows Bloom's Taxonomy (2001) for learning outcomes and includes detailed explanations, worked examples, and practice exercises.
🌐 Explore the full textbook: https://dmccreary.github.io/claude-skills/
#AI #GenAI #GenerativeAI #Education #EdTech #OpenEducation #OER #ELearning #Textbook #InteractiveTextbook #MicroSims #Visualizations #Quizzes #Geometry #Mathematics #MkDocs #ClaudeAI #LMS #CurriculumDesign #STEMeducation🎓 很高兴为大家分享一款全新的开放教育资源:专为高中生设计的交互式几何教材!
这本智能教材结合了AI辅助内容生成技术与成熟的教育框架。基于MkDocs Material构建,融入了展示概念依赖关系的学习图谱、使用p5.js的交互式MicroSims,以及全面的评估工具,让几何学习更易懂、更具吸引力。
📊 数据概览:
• 13个章节,涵盖点、线、角、三角形、多边形、圆形和3D几何
• 200个按依赖关系组织的概念
• 5个交互式MicroSims(p5.js模拟)
• 10道自测测验题目
• 22个定义精准的术语表条目
• 225000+字(约900等效印刷页数)
本项目由Claude AI技能与智能教材框架生成,展示了AI如何在保持教学质量与严谨性的同时,助力教育内容创作。
所有内容均遵循布鲁姆分类法(2001版)制定学习目标,包含详细解析、实例与练习题。
🌐 探索完整教材:https://dmccreary.github.io/claude-skills/
#AI #GenAI #GenerativeAI #Education #EdTech #OpenEducation #OER #ELearning #Textbook #InteractiveTextbook #MicroSims #Visualizations #Quizzes #Geometry #Mathematics #MkDocs #ClaudeAI #LMS #CurriculumDesign #STEMeducation📚 Just published: An AI-generated interactive textbook on Geometry for high school students!
This intelligent textbook uses MkDocs Material, learning graphs, and interactive p5.js MicroSims to make geometry engaging and accessible.
Key features:
• 13 comprehensive chapters
• 200 concepts with dependency mapping
• 5 interactive simulations
• 225,000+ words of content
• Open source and freely available
Built using Claude AI and the intelligent textbook framework - demonstrating how AI can enhance educational content while maintaining quality.
Explore it here: https://dmccreary.github.io/claude-skills/
#AI #GenAI #Education #EdTech #OpenEducation #Textbook #MicroSims #Geometry #Mathematics #ClaudeAI #STEMeducation📚 刚刚发布:由AI生成的、专为高中生设计的交互式几何教材!
这本智能教材使用MkDocs Material、学习图谱和交互式p5.js MicroSims,让几何学习更具吸引力、更易懂。
核心特色:
• 13个内容全面的章节
• 200个带依赖关系映射的概念
• 5个交互式模拟
• 225000+字的内容
• 开源且免费获取
基于Claude AI与智能教材框架构建——展示了AI如何在保持质量的同时提升教育内容。
立即探索:https://dmccreary.github.io/claude-skills/
#AI #GenAI #Education #EdTech #OpenEducation #Textbook #MicroSims #Geometry #Mathematics #ClaudeAI #STEMeducation🎓 New open educational resource: Interactive Geometry textbook for high school!
✨ 13 chapters | 200 concepts | 5 MicroSims | 225K words
AI-generated using Claude and MkDocs Material. Free and open source.
📖 https://dmccreary.github.io/claude-skills/
#Education #EdTech #Geometry #AI #OpenEducation #Textbook🎓 全新开放教育资源:面向高中生的交互式几何教材!
✨ 13章 | 200个概念 | 5个MicroSims | 22.5万字
由Claude与MkDocs Material生成,开源免费。
📖 https://dmccreary.github.io/claude-skills/
#Education #EdTech #Geometry #AI #OpenEducation #Textbookscripts/linkedin-metrics-extractor.py#!/usr/bin/env python3
"""Extract metrics from book-metrics.md for LinkedIn announcements."""
import re
import yaml
def extract_book_metrics(metrics_file):
"""Parse book-metrics.md and return dictionary of metrics."""
# Implementation: Parse markdown table
pass
def extract_site_config(mkdocs_file):
"""Parse mkdocs.yml and return site metadata."""
# Implementation: Load YAML and extract site_name, site_url, etc.
pass
def format_number(n):
"""Format numbers for readability (e.g., 225182 -> 225,000)."""
# Implementation: Round and format large numbers
passscripts/linkedin-metrics-extractor.py#!/usr/bin/env python3
"""Extract metrics from book-metrics.md for LinkedIn announcements."""
import re
import yaml
def extract_book_metrics(metrics_file):
"""Parse book-metrics.md and return dictionary of metrics."""
# Implementation: Parse markdown table
pass
def extract_site_config(mkdocs_file):
"""Parse mkdocs.yml and return site metadata."""
# Implementation: Load YAML and extract site_name, site_url, etc.
pass
def format_number(n):
"""Format numbers for readability (e.g., 225182 -> 225,000)."""
# Implementation: Round and format large numbers
passundefinedundefined