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Teacher Professional Development (TPD) is a critical pathway for enhancing educational quality and supporting educators’ professional growth. With the rapid advancement of artificial intelligence (AI), AI-supported TPD has emerged as a transformative trend in educational innovation. This study employs a systematic literature review to analyze international cases from 2019 to 2024, identifying and examining key applications of AI in TPD. From a technological empowerment perspective, the study synthesizes four core application scenarios of AI-supported TPD. The findings indicate that AI primarily supports TPD through intelligent learning analytics, intelligent chatbots, intelligent online systems, and intelligent virtual spaces. By analyzing these representative scenarios, the study further proposes practical pathways and strategic implications for the future development of AI-supported TPD, offering insights to guide the digital transformation and high-quality advancement of TPD in China.

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A Systematic Review of International Studies on AI-Supported Teacher Professional Development–Extended Abstract

  • 会议论文

  • 发表日期：

    2026年

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  • Huiying Cai,
  • Jiayue Sun,
  • Bing Han

摘要

Teacher Professional Development (TPD) is a critical pathway for enhancing educational quality and supporting educators’ professional growth. With the rapid advancement of artificial intelligence (AI), AI-supported TPD has emerged as a transformative trend in educational innovation. This study employs a systematic literature review to analyze international cases from 2019 to 2024, identifying and examining key applications of AI in TPD. From a technological empowerment perspective, the study synthesizes four core application scenarios of AI-supported TPD. The findings indicate that AI primarily supports TPD through intelligent learning analytics, intelligent chatbots, intelligent online systems, and intelligent virtual spaces. By analyzing these representative scenarios, the study further proposes practical pathways and strategic implications for the future development of AI-supported TPD, offering insights to guide the digital transformation and high-quality advancement of TPD in China.