KEYNOTE I
大會專題演講一 Keynote Speech I
AI 時代的教學：守護人性、建立專業與重塑實踐 Teaching in the Age of AI: Preserving Humanity, Building Expertise, and Reimagining Practice
講者介紹 Speaker Profile
Erika Daniels 博士是美國加州州立大學聖馬可斯分校（California State University San Marcos）的讀寫教育學教授。自 1994 年以來，Erika 在公共教育領域擔任過多種教學職務，教學對象涵蓋幼稚園、初中及非傳統體制高中。在她的 K-12（幼兒園至高三）教學生涯中，她長期任教於高貧困率的城市學區，主要輔導在學業表現、學習動機或兩者皆面臨困境的學生。作為一名大學教授，Erika 的教學與研究領域相互結合，主要探討學校環境如何促進或阻礙青少年的學習動機。Erika 堅信，開展具備實用價值的研究至關重要，如此才能為教師和學校行政人員提供具體的工具與策略，進而改善學生的教育成果與身心社會發展。
Dr. Erika Daniels is a Professor of Literacy at California State University San Marcos in the United States. Since 1994 Erika has held a variety of teaching positions in public education ranging from kindergarten to middle school to alternative high school. Throughout her K-12 teaching career, she taught in high-poverty, urban school districts and worked with students who struggled in terms of academics, motivation, or both. As a university professor, Erika’s teaching and research interests intersect and focus on the ways in which the context of schooling both fosters and hinders adolescent motivation. Erika believes that it is essential to conduct research with a practical focus to provide teachers and administrators with tools and strategies for improving their students’ educational and social-emotional outcomes.
演講摘要 Abstract
人工智慧正在快速改變教學與學習的面貌。本場主題演講邀請教育工作者超越對 AI 的初步好惡反應，進而以好奇心、道德清晰度與專業判斷來應對。雖然生成式 AI 工具讓人感到新穎，但人工智慧與機器學習其實已發展數十年。理解這段更廣闊的歷史，能減緩焦慮，並協助教育者在將這些工具納入教學實踐時，做出更深思熟慮的決策。
本演講的核心是「人在迴圈」（Human-in-the-loop）框架。其目標並非取代思考，而是去理解當教育者與學生與 AI 協同工作時，思考方式會產生何種變化。不論是撰寫有效的提示詞（Prompts）、評估輸出結果、辨識不準確之處，或是判斷回應是否反映了學科知識、健全的教學法以及學習者自己的聲音，人類的專業知識依然至關重要。
本演講挑戰教育者，不僅要思考 AI 能做什麼，更要探討當學習者在這個越來越由 AI 介導的世界中前行時，他們需要練習、質疑與創造些什麼。
Artificial intelligence is rapidly changing the landscape of teaching and learning. This keynote invites educators to move beyond initial positive or negative reactions to AI and instead consider how to respond with curiosity, ethical clarity, and professional judgment. Although generative AI tools feel new, artificial intelligence and machine learning have developed over decades. Understanding that broader history can reduce anxiety and help educators make more thoughtful decisions about how these tools fit within their practice.
At the center of the talk is a human-in-the-loop framework. The goal is not to replace thinking but rather to understand how thinking changes when educators and students work alongside AI. Human expertise remains essential in crafting effective prompts, evaluating outputs, recognizing inaccuracies, and determining whether a response reflects disciplinary knowledge, sound pedagogy, and the learner’s own voice.
The talk challenges educators to ask not simply what AI can do but also what learners need to practice, question, and create as they navigate an increasingly AI-mediated world.
