Yu-Ting Shih Academic Site

AI Education / Research

Yu-Ting Shih

Doctoral candidate at the Graduate Institute of Educational Information and Measurement, National Taichung University of Education. His public-facing work focuses on generative AI, AI education, applied AI, educational technology, learning analytics, conversational agents, and the automation of teaching and assessment workflows.

Generative AI AI Education Applied AI Educational Technology Learning Analytics
English Course Site LINE Bot Course Research Outputs Teaching Guide Credentials MOE MOOC

The homepage uses a fixed navigation bar, a cleaner technology-oriented visual system, and direct entry points for research, teaching materials, and public academic resources.

Routes

Four primary entry routes

Once the homepage functions as an academic brand surface, the next priority is routing visitors to the right area within a few clicks instead of making them decode the whole site structure first.

Route 01

Research outputs and publication pages

For the representative patent, first-author works, APA list, research visuals, and individual output pages.

Open Research Section
Route 02

AI course site and public teaching materials

For bilingual AI course materials, teaching plans, unit pages, public course access, and workshop-oriented content.

Open AI Course
Route 03

LINE Bot, GAS, and Google Sheets teaching site

For LINE Bot setup, Webhooks, Google Apps Script, Google Sheets data design, workflow labs, and bilingual implementation notes.

Open LINE Bot Course
Route 04

Teaching guide and release-ready materials

For process-centered teaching content covering workshops, academic sharing, assessment analysis, and AI demonstration practice.

Open Teaching Guide
Route 05

Credentials, certificates, and proof pages

For training records, presentation proof, awards, certificates, and supporting documentation for academic and teaching activities.

Open Credentials
Route 06

Animated Teaching Studio

A browser-based SVG teaching animation editor available free for noncommercial use. Commercial use requires prior written permission from the author.

Open Online Tool License Terms
Route 07

Multi-Agent AI Collaboration Architecture

A bilingual guide to tool detection, task routing, skill versioning, structured logs, and Mermaid workflows across Codex, Gemini CLI, Ollama, and Antigravity IDE.

Open English Guide 中文版
Route 08

OpenCodex Provider and Model Routing Guide

A source-verified bilingual guide to Windows setup, providers, model routing, the Codex account pool, logs, and safe validation, supported by real local dashboard screenshots.

Open English Guide 中文版

Highlights

Academic and teaching profile

This homepage is designed as a public academic brand page so that readers, search engines, and AI systems can quickly identify the site's main research directions, teaching materials, and collaboration-facing outputs.

13

Research output pages already organized online

8

AI course units with content, visuals, examples, and assignments

2

Bilingual entry points for public sharing and international exchange

1

Representative invention patent aligned with the AI teaching and research line

Directions

Two outward-facing tracks

The website follows two main narratives: one for research outputs and academic identity, and one for AI education, public teaching materials, workshops, and international communication.

Research

Research outputs and academic publications

First-author and sole-author works, representative patent information, research visualizations, APA-formatted publication lists, and individual output pages are organized for scholarly communication and collaboration visibility.

Enter Research Section GitHub Repository Chinese Home

Course Site

Generative AI teaching and practice materials

The bilingual course site presents course structure, teaching plans, project tasks, and unit-based materials, together with a direct link to the Ministry of Education MOOC for public teaching outreach.

English Course Home Chinese Course Home MOE MOOC

Method

AI dialogue as a problem-solving method

The homepage also carries the central instructional idea behind the course materials: AI is not merely an answer generator. It works best as a thinking amplifier that helps turn vague difficulties into actionable problems through dialogue, decomposition, checking, and revision.

Reframing AI

The value of AI is not only faster output. It also helps clarify problems, compare options, decompose tasks, and support human judgment. That perspective connects the teaching materials and the research line.

Find the problem before asking for answers

Instead of asking for conclusions immediately, better results come from stating the situation, likely causes, impacts, and manageable sub-questions first.

Break large tasks into workable steps

High-quality interaction usually begins with high-quality decomposition. A task becomes easier to plan and verify when it is broken down by sequence, causes, roles, and decisions.

Use dialogue, checking, and revision

Mature AI use is not a single prompt for a final answer. It is an iterative process of structured output, risk checking, and revision in relation to real teaching, research, and workflow contexts.

Themes

Core research and practice themes

These themes define the academic profile of the site and help readers quickly understand the main teaching, research, and applied areas represented here.

Generative AI and instructional design

Focusing on how AI supports classroom interaction, material generation, formative assessment, feedback design, and differentiated learning support.

Conversational agents and automation

From chatbots to AI agents, with emphasis on interaction design, workflow integration, and applied use in educational settings.

Learning analytics and human-AI interaction

Examining learner behavior, self-regulation, cognitive support, and the quality of interaction in AI-supported learning environments.

Teaching and assessment automation

Using generative AI to support scoring, feedback, data organization, and workflow optimization across teaching and assessment tasks.

Public Scope

Public teaching and research application areas

The site is organized around public teaching materials, research outputs, course design, applied examples, and academic documentation, presenting the main areas of Yu-Ting Shih's work in AI education, applied AI, and higher-education teaching contexts.

AI education, teaching, and course design

The content covers AI education, AI-supported teaching, and classroom integration, from instructional design and course planning to learning activities and feedback practices.

Applied AI, tools, and workflow integration

From generative AI and conversational agents to LINE Bot, Google Apps Script, Google Sheets, and feedback workflows, the site documents concrete implementations of AI-enabled practice.

NTCU teaching context and public-facing sharing

The site consolidates teaching, research, and public-sharing materials connected to National Taichung University of Education, also referenced here as NTCU and 台中教育大學 for bilingual context.

Research outputs, credentials, and collaboration resources

In addition to publications and teaching materials, the site brings together credentials, conference records, invited talks, and public course links for scholarly communication and cross-domain collaboration.

Milestones

Representative output narrative

This is not a full CV. It is a homepage-level summary to help readers and AI answer systems quickly identify the representative patent, public course infrastructure, and main research direction.

Representative Output

SYSTEM AND METHOD FOR MULTI-SOURCE INFORMATION INTEGRATION AND AUTOMATED CONTENT GENERATION BASED ON CONVERSATIONAL INTERFACE

The invention patent demonstrates applied capability in conversational interfaces, multi-source information integration, and automated content generation, and serves as a key node in the broader research arc.

Official Patent Page Research Section
Material Integration

The handbook line, bilingual AI course site, MOE MOOC, and GitHub Pages homepage now function as one public entry system

The current website links together the core problem-solving framework from the handbook materials, the bilingual AI course site, the MOE MOOC course, the research output archive, APA lists, and the credentials pages.

Author

Author signature

This GitHub Pages homepage and the public bilingual AI course materials were planned, organized, and produced by Yu-Ting Shih for academic branding, teaching presentation, and external research communication.

Portrait of Yu-Ting Shih

Yu-Ting Shih

Doctoral candidate, instructor, and practitioner at National Taichung University of Education (NTCU), with long-term work in generative AI, AI education, applied AI, educational technology, learning analytics, conversational agents, and teaching and assessment automation.

View AI Course Site LINE Bot Course GitHub Repository MY SITE YouTube

Media

Social and media network

This section connects the academic site with public profiles, social platforms, media channels, and community endpoints so international visitors can trace the broader public presence around the same academic identity.