AI在教育研究領域的應用系列（七）：Notion AI在文獻資料庫之應用實測

Applications of AI in Educational Research Series (VII): Exploring the Use of Notion AI in Literature Database Management

人工智慧（Artificial Intelligence, AI）與生成式人工智慧（Generative AI, GenAI）的應用與日俱增，在教育領域的研究應用亦日益廣泛。本文旨在探討數位工作平台Notion與其提供的人工智慧功能Notion AI在文獻計量分析流程中的應用，並聚焦於文獻資料庫的建構與管理。首先介紹Notion與Notion AI的基本操作，並以Scopus資料庫所匯出的書目資料檔案為例，實測其在資料匯入、自動翻譯、屬性標記與文獻篩選流程中的實務操作與效益。透過實例示範，本研究指出Notion與Notion AI之結合應用，能有效提升文獻處理效率及文獻篩選透明度，展現新興數位工具在支援文獻計量分析與系統性研究回顧的潛力，進而促進人工智慧技術於學術知識生產流程中的整合與創新。

The advancement of Artificial Intelligence (AI) and Generative AI (GenAI) is accelerating, and their research applications in the field of education are becoming increasingly widespread. This article explores the potential of the digital workspace platform Notion and its built-in AI feature, Notion AI, in supporting bibliometric analysis– specifically in constructing and managing literature databases. The article begins by introducing the basic operations of Notion and Notion AI. Using bibliographic data exported from the Scopus database as an example, it examines these tools’ practical use and benefits in data import, automatic translation, property tagging, and literature screening. Through hands-on demonstrations, the study shows that integrating Notion with Notion AI can significantly improve the efficiency of literature processing and enhance the transparency of the screening process. The findings highlight the potential of emerging digital tools in facilitating bibliometric analysis and systematic reviews, ultimately fostering the integration and innovation of AI technologies within academic knowledge production.