NTCU AI Education Course Site
Created by Yu-Ting Shih | Public AI education and applied AI course materials from National Taichung University of Education (NTCU)
This site is an original public-facing course version rebuilt from AI-related materials in classfile.
It focuses on AI education, AI applications, generative AI teaching, and higher-education classroom practice.
It does not reproduce the structure or premium dialogue-based content from your paid materials. Instead, it offers a fresh learning path for international readers, collaborators, and workshop participants.
Current Positioning
This course site was organized and produced by Yu-Ting Shih. It now follows the same fixed-header, tech-minimal interface as the main academic site.
MOOC Course
This course is also available on the Ministry of Education's MOOC platform as a formal public-facing course entry, allowing readers to review the syllabus, videos, and enrollment information outside this website.
Institution: National Taichung University of Education
Certified hours: 4 hours | Audience: Higher education | Open since March 31, 2025
The course introduces Python step by step, including libraries, educational data analysis, data visualization, and simple inferential statistics.
Sourcebook Edition
This update draws on the expanded sourcebook edition of AI時代，我與它的對話 and maps its core chapter logic and classfile slide materials back into the eight-unit course structure.
Capability Loop
The long-form sourcebook does not treat AI as a shortcut to instant answers. Its central claim is that learners need to notice problems, break them down, work through dialogue, and validate judgment. That capability arc is now made explicit on this homepage.
AI works best as a thinking amplifier. The real difference lies in interaction habits, judgment, and responsibility.
Move from symptoms and complaints to a clearer problem statement, likely causes, and smaller, actionable questions.
Use time, causality, perspective, and decision criteria to make large tasks easier to begin and improve.
Use iterative prompting, structured output, and risk checking so AI supports thinking rather than replacing human judgment.
Reading Modes
The sourcebook frames the content as personal training, classroom material, and workshop handout. This course site now follows the same logic so instructors and readers can adapt it to different settings.
Public Boundary
This website edition preserves the knowledge structure, interaction logic, and method-oriented cases of the sourcebook, while avoiding direct reuse of longer premium dialogues, full scripts, and future paid-only depth materials.
Video Entry
Readers who want a more direct demonstration format can move from this course site into Yu-Ting Shih's YouTube channel. The channel home, video archive, stream archive, and playlists make it easier to switch between reading, watching, and replaying classroom-oriented examples.
Learning Path
The course follows a clear sequence: conceptual grounding, prompt design, tool choice, teaching application, research application, workflow integration, interactive services, and governance.
Build a stable mental model for generative AI, multimodal systems, and agent-based applications.
Turn vague requests into structured prompts and reusable interaction patterns.
Select platforms according to task type, output needs, and collaboration context.
Translate tools into concrete classroom, research, and administrative workflows.
Units
Each unit includes learning goals, activity ideas, reflection tasks, and implementation suggestions, while also aligning with the sourcebook's capability steps of understanding AI, finding problems, decomposing tasks, dialoguing with AI, integrating workflows, and managing risk.
Understand how AI changes the way people work, learn, and make decisions.
Unit 2Build reusable prompt structures and improve output control.
Unit 3Compare chat, research, productivity, and workflow-oriented tools.
Unit 4Use AI to support lesson planning, assessment, feedback, and classroom interaction.
Unit 5Explore literature review, idea development, writing support, and research workflows.
Unit 6Turn documents, forms, spreadsheets, and AI tools into repeatable systems.
Unit 7Move from single prompts to service-oriented AI experiences.
Unit 8Build governance habits for accuracy, privacy, bias, and publishing boundaries.
Public Version
This English version, produced by Yu-Ting Shih, is meant for international exchange and public communication. It emphasizes methods and structure while protecting premium content, exclusive scripts, and deeper dialogue examples reserved for future paid offerings.
Publishing
The site now follows a static-site structure with root-level entry pages, unit subpages, shared CSS, and local assets, which makes it straightforward to publish through GitHub Pages.
Original Figures
Practice Screens
These interface references come from classfile slide materials and make the course feel closer to real classroom practice.
PDF Materials
These first-page visuals come from PDF handouts and lecture decks stored in classfile and now help frame the teaching scenarios, platform introductions, and research-oriented examples in the public course site.
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