Yu-Ting Shih Academic Site

First-Author Works

First-Author and Sole-Author Works of Yu-Ting Shih

This section presents Yu-Ting Shih’s first-author and sole-author works in generative AI, AI education, AI applications, educational technology, and learning analytics, including a patent, conference presentations, and journal-related outputs through bilingual web pages, an ENA relationship map, a research radar chart, a phase-centroid comparison, a readable research-development timeline, and APA-style lists.

Author: Yu-Ting Shih First Author Sole Author Bilingual Presentation

This page combines formal citations, thematic visualization, and links to existing research pages so that representative works and the broader research trajectory can be viewed together.

View APA List Chinese Page View Credentials
ENA research relationship map

This ENA relationship map highlights the co-occurrence structure among major research themes, including generative AI, assessment, agent systems, reading literacy, and higher-education teaching contexts.

Featured Output

Representative output

The patent is presented here as a representative output that connects later work on generative AI teaching, conversational interfaces, automated feedback, and workflow integration.

Patent I918530

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

Shih, Y.-T. (2026). SYSTEM AND METHOD FOR MULTI-SOURCE INFORMATION INTEGRATION AND AUTOMATED CONTENT GENERATION BASED ON CONVERSATIONAL INTERFACE (I918530). Taiwan Intellectual Property Office, Ministry of Economic Affairs.

View official patent page

This patent represents a system-level outcome in Yu-Ting Shih’s research trajectory, integrating conversational interfaces, multi-source information, content generation, and automated workflows into a practical methodological framework.

Research radar chart

The radar chart summarizes the main distribution of themes across generative AI, AI education, workflow design, automated scoring, conversational agents, and learning analytics.

Research phase comparison

The phase-centroid comparison visualizes the thematic centers of 2015, 2023, 2025, and 2026, showing how the work develops from foundational learning studies to GenAI teaching interaction and human-machine collaborative assessment.

Research Timeline

Research development trajectory

The timeline below summarizes how the research evolves from core teaching-and-learning questions toward AI acceptance, generative AI-supported interaction, collaborative assessment, and broader cross-context applications.

2015 Foundation phase

  • Self-regulated learning
  • Learning outcomes
  • Cognitive load

This phase established the baseline for later teaching-and-learning research.

2023 Acceptance and attitude phase

  • Technology acceptance
  • Usage intention
  • Learning outcomes

The focus shifted to cognition and attitudes toward AI applications.

2025 GenAI teaching interaction phase

  • Generative AI
  • Programming
  • Data science
  • Human-AI collaboration

This phase centers on AI-supported learning interaction.

2026 Human-machine collaborative assessment expansion

  • Automated scoring
  • Scoring consistency
  • Bias and calibration
  • Learning scaffolds
  • Computational thinking

The work expands from teaching applications into integrated assessment.

Extended applications

  • Agent systems
  • Virtual students
  • Social-emotional assessment
  • Reading literacy

These themes form a cross-context application branch beyond the core line.

Works

First-author and sole-author works

The items below are organized by year and theme, with a focus on generative AI, AI education, AI applications, educational technology, learning analytics, and higher-education teaching practice at NTCU. Where a detailed page already exists in the repository, the entry links directly to that page.

2026 | Reliability and Difference Analysis of GenAI Human-Machine Collaborative Assessment

Shih, Y.-T., & Chang, D.-C. (2026, June 6). 7th Taiwan Conference on Business Education and Management, Tainan, Taiwan.

This study examines reliability and scoring differences in GenAI-supported human-machine collaborative assessment and extends the research line on AI-based educational evaluation and feedback.

Open research page

2026 | Satisfaction and Needs Analysis of a Generative AI Automated Scoring and Feedback System

Shih, Y.-T., & Chang, D.-C. (2026, May 20). 2026 ICEET International Conference, Taipei, Taiwan.

This work focuses on the satisfaction, needs, and acceptance of a generative AI automated scoring and feedback system in higher education.

Open research page

2026 | Development and Effectiveness Analysis of a Lightweight Serverless AI Agent for Optimizing Learning Workflows

Shih, Y.-T., & Lin, Y.-C. (2026, May 15). Engineering, Technology, and STEM Education Conference, Taichung, Taiwan.

This study examines how lightweight serverless AI agents can be integrated into learning workflows and educational tasks.

Open research page

2026 | From Mind Blindness to Flow

Shih, Y.-T., & Li, C.-H. (2026, March 5-6). TWELF 2026, Nantou, Taiwan.

This presentation connects computational thinking with cognitive compensation and the benefits of generative AI interaction.

Open research page

2025 | Application of a Lightweight Serverless AI Agent for Optimizing Teaching Contexts and Learning Efficiency

Shih, Y.-T., & Li, C.-H. (2025, October 31-November 2). APERA-TERA 2025, Kaohsiung, Taiwan.

This work extends AI agent design into classroom workflow optimization and learning-efficiency improvement.

Open research page

2025 | Application of Intelligent Dialogue Systems in Psychological and Social-Emotional Assessment

Shih, Y.-T., Wang, W.-H., & Li, C.-H. (2025, October 24-25). Chinese Testing Society Annual Meeting, Tainan, Taiwan.

This study extends conversational systems into psychological and socio-emotional assessment settings.

Open research page

2025 | From Traditional Semantic Analysis to Generative AI

Shih, Y.-T., Tseng, C.-J., Chang, M.-H., & Kuo, C.-L. (2025, October 10-12). TANET 2025, Yilan, Taiwan.

This work connects generative AI with cybersecurity and privacy issues in cloud-based educational task automation.

Open research page

2025 | Behavioral Analysis of Human-AI Interaction in AI-Assisted Programming and Data Science Learning

Shih, Y.-T., & Li, C.-H. (2025, June 4). ICEET 2025, Taipei, Taiwan.

This study analyzes learners’ interaction patterns when AI is used to support programming and data science learning.

Open research page

2025 | Duration Effects of Introducing Generative AI into a Data Science Course

Shih, Y.-T. (2025, May 24). Taiwan Business Education and Management Conference, Tainan, Taiwan.

This sole-author work examines how different intervention lengths affect learning outcomes among non-CS undergraduates.

Open research page

2025 | Enhancing Learning Outcomes and Reducing Anxiety in Programming Courses Through AI Integration

Shih, Y.-T., Li, C.-H., & Chen, H.-R. (2025, January 10-12). ICAEIT 2025, Fukuoka, Japan.

An early international presentation in Yu-Ting Shih’s generative AI teaching line, focusing on programming learning and anxiety reduction.

Open research page

2018 | Design and Learning Effectiveness Analysis of an Instant Adaptive Virtual Teaching Assistant

Shih, Y.-T., & Chen, H.-R. (2018, March 23-24). TWELF 2018, Taichung, Taiwan.

This early work foregrounds adaptive teaching support and virtual assistance, themes that later develop into conversational and AI-assisted educational systems.