AIGC 數位學習新思維:以 Padlet 與 AI 鷹架建構學生的學習自主學習歷程
講者/Speaker： 陳泓曄, 高抬主, Chen, HungYeh ; Kao, TaiChu
本課程以「AIGC 數位學習新思維」為核心，開創一套「教師引導簡報 ➔ AI 雙引擎驅動（NotebookLM + Gemini） ➔ Padlet 歷程管理」的創新自主學習數位鷹架。課程設計採取「示範－模仿－實作」為主軸，將教師的教學策略封裝於非同步自學簡報中，引導學生在 Padlet 平台上建立結構化的自學基地，本質上降低了新高一生面對自主學習時的「空白頁效應」與迷惘感。
課程創新地以《原子習慣》行為科學作為自學導讀核心。學生不論使用線上電子教材或將實體書掃描上傳，皆先透過 NotebookLM 建立封閉式知識庫，在「零 AI 幻覺」的安全環境下精讀文本、抓取核心摘要；隨後切換至 Google Gemini 作為行為教練，將宏大的目標動態拆解為每日 10 分鐘或半小時的微行動。
本方案不僅引導學生全員產出驚人的跨域數位成果（如 LINE 貼圖上架、學科互動遊戲網頁、高等數學矩陣與大數據延伸探究），更實證了「學習遷移」的發生，並且學生成功將這套 AIGC 邏輯與問題拆解能力，遷移至日常艱澀學科的系統化複習與自我管理中。
最重要的是，本教學模式具備極高的推廣價值與可複製性，能直接作為全台灣「自主學習指導教師」或導師的數位減負大禮包。透過 AI 輔助與精密流程設計，解放現場教師有限的輔導人力，真正落實「師生人機共好」與素養教育的終極目標。
Centering on the core vision of "New Thinking in AIGC Digital Learning," this curriculum introduces an innovative digital scaffolding ecosystem for high school autonomous learning, driven by a "Teacher-Guided Instructional Deck ➔ Dual-AI Engine (NotebookLM + Gemini) ➔ Padlet Progress Management" framework. By structuring the instructional design around the workflow of "Demonstration – Imitation – Practice," the course encapsulates pedagogical strategies within an asynchronous self-study deck. This approach guides students to establish structured autonomous learning hubs on Padlet, fundamentally mitigating the "blank-page effect" and the sense of uncertainty commonly experienced by tenth-grade freshmen.The curriculum uniquely adopts the behavioral science principles of Atomic Habits as its core reading guide. Whether utilizing curated online digital textbooks or uploading scanned copies of physical books, students first import their materials into NotebookLM to construct a closed knowledge base, enabling intensive text reading and summary extraction within a "zero-AI-hallucination" secure environment. Subsequently, students transition to Google Gemini, which serves as a personal behavioral coach, to dynamically break down macro-level goals into executable 10-minute daily micro-actions.This program not only guides all participating students to generate impressive cross-disciplinary digital artifacts (such as publishing personal LINE stickers, developing interactive academic review web games, and conducting advanced extensions into high school matrices and big data analytics) but also empirically demonstrates the occurrence of "learning transfer." Students successfully transfer the acquired AIGC logic and problem-deconstruction capabilities into systematic subject reviews and daily self-management. Most importantly, this instructional model possesses high generalizability and can be seamlessly replicated by autonomous learning supervisors and homeroom teachers across Taiwan as a digital workload-reduction toolkit. By leveraging AI assistance alongside precise workflow design, this curriculum alleviates the constraints of limited teacher counseling capacity, truly achieving the ultimate goal of "Teacher-Student Human-AI Synergy" and competency-based education.