參與 IEEE International Conference on Big Data Computing Service and Machine Learning Applications，對我而言不僅是一次深入了解國際大數據與機器學習前沿發展的契機，更是一次深具啟發的學術交流經驗。在會議中，我有幸與大會主席 Iraklis Varlamis 教授（Harokopio University of Athens, Department of Informatics and Telematics） 進行面對面的討論。他特別建議，若能在未來的 IEEE BigData Service 會議中增設「教育大數據應用（Educational Big Data Applications）」徵稿主題，並邀請資訊教育領域的學者共同參與，將能擴大影響力，並為國際學界開啟新的合作契機。
這樣的交流讓我深受啟發。回國後，我立即開始思考如何讓 Uedu 優學院 的研究能量與台灣的教育大數據研究更緊密結合。我開始逐步推動成立一個跨校跨域的正式學會，期望能將優學院既有的研究成果與團隊力量擴散出去，並吸引更多研究者共同投入。這個構想最終凝聚成為 「台灣人工智慧多模態學習分析研究學會（TAIMS, Taiwan AI and Multimodal Learning Analytics Society）」。
目前學會仍位於籌備階段，但已獲得許多學者的積極響應與支持，逐步形成一個多元且跨領域的研究社群。TAIMS 將以優學院的多模態學習歷程資料為核心，建構一個完整的研究循環鏈：「資料擷取（Uedu 平台）→ 分析（學會協助研究與合作）→ 呈現（學術期刊與國際會議發表）」。未來，學會不僅會舉辦工作坊、釋出新工具、開放部分數據資源，還將成為台灣教育大數據與 AI 學習分析的重要交流平台，幫助更多教師與研究人員提升研究能量。
這場會議經驗讓我更深刻地意識到，台灣在教育大數據的發展若能透過學會作為樞紐，把資料、人才、與國際交流緊密結合，就能打造一個具有持續影響力的研究生態系。這也是我推動 TAIMS 的最大動力。希望未來能與更多教育工作者與學者攜手合作，把台灣的經驗推向國際，並在數位學習與人工智慧的交會處，發出屬於我們的聲音。
Participating in the IEEE International Conference on Big Data Computing Service and Machine Learning Applications was not only an invaluable opportunity for me to gain deeper insights into the cutting-edge developments of big data and machine learning worldwide, but also a truly inspiring academic exchange experience. During the conference, I had the privilege of engaging in a face-to-face discussion with Professor Iraklis Varlamis (Harokopio University of Athens, Department of Informatics and Telematics), the conference chair. He specifically suggested that introducing a new track on “Educational Big Data Applications” in future IEEE BigData Service conferences, while inviting scholars from the field of information and education, could significantly broaden the conference’s influence and create new opportunities for international collaboration.
This exchange offered me profound inspiration. Upon returning to Taiwan, I began to reflect on how to more closely connect the research capacity of Uedu Academy with the broader field of educational big data research. I initiated steps to establish a formal cross-institutional and interdisciplinary society, aiming to amplify Uedu’s existing achievements and research team capacity while attracting more researchers to participate. This vision has gradually crystallized into the foundation of the Taiwan AI and Multimodal Learning Analytics Society (TAIMS).
Although the society is still in its preparatory stage, it has already received enthusiastic responses and support from numerous scholars, gradually shaping a diverse and interdisciplinary research community. TAIMS will leverage the multimodal learning trace data collected by Uedu as its core, building a comprehensive research cycle: data acquisition (via the Uedu platform) → analysis (supported by the society’s research collaborations) → dissemination (through academic journals and international conferences). Looking ahead, TAIMS plans to organize workshops, release research tools, open selected datasets, and serve as a vital exchange platform for educational big data and AI-driven learning analytics in Taiwan, empowering more teachers and researchers to enhance their scholarly impact.
This conference experience deepened my realization that Taiwan’s development in educational big data can be significantly strengthened by using a society as a hub to closely integrate data, talent, and international collaboration. Such an ecosystem would foster sustainable academic influence. This has become the driving force behind my efforts to promote TAIMS. I look forward to working with more educators and researchers in the future, bringing Taiwan’s experiences onto the international stage and ensuring our voice is heard at the intersection of digital learning and artificial intelligence.
