High Satisfaction from Students on Core Features核心功能獲得學生高度滿意
StashTag’s pilot shows clear, positive impact where it matters most: turning fleeting confusion into timely clarity without disrupting teaching. Across a one-semester deployment spanning 59 lectures and 487 students, engaged users rated the Stashing Button highly for usefulness (M=4.07/5) and convenience (M=4.02/5). Among students who used AI-generated Stashed Notes, perceived quality (M=4.17/5), usefulness (M=4.29/5), and convenience (M=4.13/5) were all strong, with many noting that summaries “condense material into key points for rapid review” and help “revisit areas of uncertainty.” The review questions that accompany these summaries earned similarly high marks for quality (M=4.25/5), convenience (M=4.09/5), and usefulness (M=4.18/5), reinforcing StashTag’s ability to both explain concepts and help students actively test understanding.
StashTag 的試行計畫在關鍵領域展現了清晰、積極的影響：在不干擾教學的前提下，將轉瞬即逝的困惑轉化為及時的清晰理解。在一學期涵蓋 59 堂課與 487 名學生的實施過程中，積極使用者對「暫存按鈕」的實用性（平均 4.07/5）與便利性（平均 4.02/5）給予高度評價。在使用過 AI 生成的「暫存筆記」的學生中，對其感知品質（平均 4.17/5）、實用性（平均 4.29/5）和便利性（平均 4.13/5）的評價均十分強勁，許多人指出摘要能「將教材濃縮為重點以供快速複習」，並有助於「回顧不確定的領域」。伴隨這些摘要的複習問題在品質（平均 4.25/5）、便利性（平均 4.09/5）和實用性（平均 4.18/5）方面也獲得了同樣的高分，強化了 StashTag 既能解釋概念，又能幫助學生主動檢驗理解的能力。
Stashing Distribution暫存標記分佈圖
The overall distribution for PHYS1112 Lecture 3 is broad, indicating that students are confused about different topics. Personalized stashed notes can address these individual needs, while the prominent peaks highlight common issues the professor can target specifically.
PHYS1112 第三堂課的整體分佈廣泛，表明學生對不同主題感到困惑。個人化的暫存筆記能滿足這些個別需求，而顯著的峰值則凸顯出教授可以特別針對的常見問題。
Students' rating學生評分
The quality of the stashed notes (then called “confusion summaries”) and the review questions is ensured by the lecture context and our RAG pipeline.
暫存筆記（當時稱為「困惑摘要」）與複習問題的品質，由課程內容背景及我們的 RAG（檢索增強生成）流程確保。
Actionable Analytics for Instructors without Extra Work為教師提供可執行的分析，無需額外工作
Crucially, StashTag bridges instructor–student blind spots with data, not disruption. After lectures, anonymized confusion peaks give professors a precise, immediate map of where comprehension dipped, with instructors describing the AI-generated outputs as “good quality” and containing “additional and correct information” beyond the lecture. The system’s keyword tagging, RAG-enhanced diagrams from official notes, and searchable summaries streamline targeted follow-up. This creates a practical loop: students log confusion in one click; StashTag delivers anchored summaries and practice; instructors receive digestible analytics that inform timely clarifications without adding significant workload.
關鍵在於，StashTag 以數據（而非干擾）來彌合師生間的認知盲點。課後，匿名的困惑峰值圖為教授提供一份精確、即時的理解落差地圖。教師們形容 AI 生成的輸出「品質良好」，且包含「課堂之外的額外正確資訊」。系統的關鍵字標記、從官方筆記經 RAG 增強的圖表，以及可搜尋的摘要，讓針對性的後續追蹤更為流暢。這形成了一個實用的循環：學生一鍵記錄困惑；StashTag 提供有據可循的摘要與練習；教師收到易於理解的數據分析，據以進行及時的澄清，卻無需增加顯著的工作負擔。
Proven Fit for Fast-Paced STEM Courses經實證適合快節奏的 STEM 課程
The pilot’s strongest signal is alignment between user sentiment and product value. Students appreciated the speed and simplicity of the Stashing Button when it worked smoothly, favored concise, timestamped explanations for quick review, and found review questions helpful for reinforcing concepts, matching the core promise to combat confusion accumulation. Instructors recognized the summaries’ pedagogical quality and the potential of AI-generated questions to ease preparation. Taken together, these results show StashTag as an immediately useful, high-satisfaction companion to live teaching: it converts hidden confusion into actionable insight, delivers clear remediation that students rate highly, and equips instructors with focused, data-driven follow-ups. For STEM courses where lecture pace is high and comprehension gaps are costly, StashTag is a convincing, ready-to-use solution that connects people through timely, AI-assisted clarity.
此試行計畫最有力的信號，是用戶感受與產品價值的高度契合。學生們欣賞「暫存按鈕」在運作順暢時的速度與簡便性，偏好簡潔、附帶時間標記的解釋以利快速複習，並認為複習問題有助於鞏固概念，這正符合了「對抗困惑累積」的核心承諾。教師們認可摘要的教學品質，以及 AI 生成問題在減輕備課負擔方面的潛力。總體而言，這些結果顯示 StashTag 是一個能立即應用、獲得高度滿意度的現場教學夥伴：它將隱藏的困惑轉化為可執行的洞察，提供受學生高度評價的清晰補救措施，並為教師提供聚焦的、數據驅動的後續行動方案。對於教學節奏快、理解落差代價高的 STEM 課程而言，StashTag 是一個令人信服、開箱即用的解決方案，透過 AI 輔助的及時明晰化，將人們連結在一起。
