Publications-Periodical Articles

Article View/Open

Publication Export

Google ScholarTM

NCCU Library

Citation Infomation

Related Publications in TAIR

題名 AI在教育研究領域的應用系列(十):AI Agents應用程式開發與後設分析取向的結構方程模型中相關係數矩陣建構
作者 吳政達;張瓊文;張漢堯
貢獻者 教政所
關鍵詞 AI代理; 人工智慧(AI); 後設分析取向的結構方程模型
AI agents; artificial intelligence (AI); MASEM
日期 2025-08
上傳時間 24-Sep-2025 09:38:52 (UTC+8)
摘要 本文旨在探討利用AI Agents應用程式開發,並聚焦在簡化MASEM矩陣的原始資料建構流程。透過設計符應建構矩陣的指令與簡易的設定,且利用一篇MASEM論文進行實測,經實測結果發現,利用AI Agents可協助從事MASEM研究者快速且正確地擷取效果值,展示了AI Agents在MASEM矩陣建構的效益。本文認為在AI技術持續進化下,研究者應保持更開放的心態,透過人機協作,將繁雜的事交給AI,將精力集中於研究結果的洞見中,在研究者持續開發下,學術研究工具將邁向更智慧化的時代。
This study aims to explore the development of AI agent applications, with a specific focus on streamlining the raw data construction process for MASEM matrices. Through the design of instructions tailored for matrix construction and simplified configurations, coupled with empirical testing using a published MASEM study, the results demonstrate that AI agents can assist MASEM researchers in rapidly and accurately extracting effect sizes. This research showcases the efficacy of AI agents in MASEM matrix construction. The findings suggest that as AI technology continues to evolve, researchers should maintain a more open mindset and embrace human-AI collaboration, delegating complex tasks to AI while concentrating their efforts on deriving insights from research outcomes. With continued development by researchers, academic research tools are advancing toward an increasingly intelligent era.
關聯 教育研究月刊, No.376, pp.116-134
資料類型 article
DOI https://doi.org/10.53106/168063602025080376008
dc.contributor 教政所
dc.creator (作者) 吳政達;張瓊文;張漢堯
dc.date (日期) 2025-08
dc.date.accessioned 24-Sep-2025 09:38:52 (UTC+8)-
dc.date.available 24-Sep-2025 09:38:52 (UTC+8)-
dc.date.issued (上傳時間) 24-Sep-2025 09:38:52 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/159628-
dc.description.abstract (摘要) 本文旨在探討利用AI Agents應用程式開發,並聚焦在簡化MASEM矩陣的原始資料建構流程。透過設計符應建構矩陣的指令與簡易的設定,且利用一篇MASEM論文進行實測,經實測結果發現,利用AI Agents可協助從事MASEM研究者快速且正確地擷取效果值,展示了AI Agents在MASEM矩陣建構的效益。本文認為在AI技術持續進化下,研究者應保持更開放的心態,透過人機協作,將繁雜的事交給AI,將精力集中於研究結果的洞見中,在研究者持續開發下,學術研究工具將邁向更智慧化的時代。
dc.description.abstract (摘要) This study aims to explore the development of AI agent applications, with a specific focus on streamlining the raw data construction process for MASEM matrices. Through the design of instructions tailored for matrix construction and simplified configurations, coupled with empirical testing using a published MASEM study, the results demonstrate that AI agents can assist MASEM researchers in rapidly and accurately extracting effect sizes. This research showcases the efficacy of AI agents in MASEM matrix construction. The findings suggest that as AI technology continues to evolve, researchers should maintain a more open mindset and embrace human-AI collaboration, delegating complex tasks to AI while concentrating their efforts on deriving insights from research outcomes. With continued development by researchers, academic research tools are advancing toward an increasingly intelligent era.
dc.format.extent 110 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) 教育研究月刊, No.376, pp.116-134
dc.subject (關鍵詞) AI代理; 人工智慧(AI); 後設分析取向的結構方程模型
dc.subject (關鍵詞) AI agents; artificial intelligence (AI); MASEM
dc.title (題名) AI在教育研究領域的應用系列(十):AI Agents應用程式開發與後設分析取向的結構方程模型中相關係數矩陣建構
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.53106/168063602025080376008
dc.doi.uri (DOI) https://doi.org/10.53106/168063602025080376008