Uedu 優學院為一個兼具教學服務與教育科技研究的平台。 本頁公開揭露平台之 Umbrella IRB 研究倫理框架、資料使用範圍與您的權利， 以保障每一位師生的知情與選擇權。 Uedu is an educational technology platform serving both teaching and research purposes. This page publicly discloses our Umbrella IRB ethics framework, data usage scope, and the rights of every user, safeguarding informed choice for all faculty and students.
本平台的研究活動統整於一份 umbrella 研究倫理審查計畫書之下， 涵蓋平台所有回溯性資料分析與新蒐集之研究活動。 All research activities on this platform are governed by a single umbrella IRB protocol, covering both retrospective analyses of existing data and prospective new data collection.
並非所有平台上的活動都屬於研究範疇，也並非所有研究活動都在 umbrella 涵蓋之內。 本框架將研究活動依據研究者對資料的接觸層級，分為三個層次。 Not every platform activity constitutes research, and not every research activity is covered by this umbrella. The framework classifies research activities into three tiers based on the investigator's level of data access.
所有 Uedu 教師研究者可直接依循本框架執行，無需另行申請 IRB。 資料一律透過 Uedu Lab 系統自動去識別化後匯出。 Any Uedu-affiliated faculty researcher may conduct these activities under this framework without filing a separate IRB. Data are always exported through Uedu Lab after automated de-identification.
涉及敏感資料個人層級接觸之特定研究活動，已在本案中逐項審查。 僅限本案計畫主持人執行，其他研究者不可援引。 Activities requiring individual-level access to sensitive data, reviewed item-by-item in this protocol. Only the PI of this protocol may conduct these; other researchers cannot invoke the umbrella.
超出上述 A、B 已定義之研究活動類型，或偏離標準 SOP 之實驗設計。 需由該教師研究者自行向其所屬機構申請 IRB。 Activities falling outside Tier A / B, or experimental designs deviating from standard SOPs. The investigator must file an IRB application with their own institution.
本平台的研究倫理框架有幾項與一般 IRB 不同的特色設計，由平台層級直接實作， 為所有使用者與研究者提供統一的技術性保護。 Several design features distinguish this framework from conventional IRB setups: they are implemented at the platform level, providing uniform technical protection to every user and researcher.
所有 A 類研究之資料一律透過 Uedu Lab 匯出介面進行。 系統自動移除姓名、學號等直接識別符，並依資料敏感度採取聚合或 k-anonymity 處理。 研究者不會拿到個人層級的識別資料。 All Tier-A data must be exported through the Uedu Lab interface. The system automatically strips direct identifiers (name, student ID) and applies aggregation or k-anonymity according to data sensitivity. Researchers never receive individually identifiable data.
針對性別認同等高度敏感屬性的研究（如多元性別深度訪談）， 採用系統仲介招募機制：學生需主動閱讀研究說明並明確勾選「同意向研究者揭露本人之性別認同」， 研究者始得知曉其身分。在學生主動揭露前，PI 無法得知其敏感屬性。 For studies involving highly sensitive attributes such as gender identity (e.g., gender-diversity interviews), the platform mediates recruitment: students must read the study description and explicitly opt in to "disclose my gender identity to the researcher" before the PI can learn their identity. Until voluntary disclosure, the PI has no access to the sensitive attribute.
性別認同、性傾向等高度敏感資料，於平台內採用 Application Layer Encryption（ALE）儲存。 即便是計畫主持人，也無法直接解密個人層級資料，僅能透過群體聚合統計進行分析。 Highly sensitive data such as gender identity and sexual orientation are stored under Application-Layer Encryption (ALE). Even the PI cannot decrypt individual-level records; only aggregate statistics are accessible for analysis.
量化分析結果以群體層級統計值呈現，不報告個體層級數據。 當特定類別的樣本數過少時，系統採用 k-anonymity 原則合併報告，避免透過準識別符反推個人身分。 Quantitative results are reported at group level, never as individual data points. When a category's sample size falls below threshold, the system merges categories under k-anonymity to prevent re-identification via quasi-identifiers.
研究資料以研究編碼標記，分析時不與課程成績連結。 是否參與研究、資料是否授權使用，完全不影響您的修課權益與成績評量。 Research data are tagged with research codes and never linked to course grades during analysis. Participation (or non-participation) in research has no bearing on enrollment status or grade evaluation.
使用者可隨時於個人設定中撤銷研究同意。 撤銷後，您的資料將自動從後續的研究匯出中排除， 已完成分析且已發表的聚合統計結果則無法回溯。 Users may withdraw research consent at any time from their account settings. After withdrawal, their data are automatically excluded from future research exports; aggregate results already analyzed and published cannot be retrospectively recalled.
平台同時服務於教學與研究兩項目的， 因此資料保存策略採雙軌分流，避免教學歷程因研究結案而被誤刪。 Because the platform serves both teaching and research purposes, data retention is split into two tracks to prevent teaching records from being erased when a research project closes.
| 資料類別Data Category | 保存期限Retention Period | 說明Notes |
|---|---|---|
|
平台學習歷程
AI 對話、作業、問卷、學習特質等 Learning records on platform AI dialogues, assignments, surveys, learner traits |
永久保存 Permanent retention | 屬於使用者個人學習檔案，永久保存為使用者自己的學習履歷，不因研究結案而刪除。 Part of the user's personal learning portfolio; retained permanently as a learning record and not erased when a research project concludes. |
|
研究匯出資料集
Uedu Lab 去識別化後之匯出檔案 Research export datasets De-identified files exported via Uedu Lab |
資料產生後 5 年內 可匯出 Exportable within 5 years of data creation | 透過 Uedu Lab 系統自動管控匯出時效，超過時限之原始歷程不再開放匯出。 Uedu Lab automatically enforces the export window; raw records beyond the window are no longer exportable. |
|
非平台研究資料
訪談錄音、逐字稿、已匯出之研究資料集 Off-platform research materials Interview recordings, transcripts, exported datasets |
研究結案後 5 年 5 years post-closure | 依研究倫理委員會規範，屆期由研究團隊人工銷毀。 Per IRB regulations, the research team manually destroys these materials upon expiry. |
| IRB 審查文件 IRB review documents | 永久保存 Permanent | 含計畫書、知情同意書、修正對照表等，供機構存查與研究稽核。 Includes protocols, consent forms, and amendment tracking, retained for institutional record and audit. |
本 umbrella IRB 同時涵蓋「回溯性」與「前瞻性」兩類資料： 既已累積的歷史學習歷程、以及 IRB 核准後新產生的資料，皆屬於研究範圍。 This umbrella IRB covers both retrospective and prospective data: historical learning records already accumulated, and new records generated after IRB approval.
平台自上線至本 IRB 核准日之前所累積的既有學習歷程。
核准日當下之快照為：
AI 對話歷程 2,442 筆、平台使用者 3,000 人以上。
此為一份已固定的歷史資料集，不會再向前擴張。
Learning records accumulated from platform launch until the IRB approval date.
Snapshot on approval day: 2,442 AI dialogue logs and over 3,000 registered users.
This is a fixed historical dataset and will not expand backward in time.
IRB 核准之後，平台仍持續營運、學生持續使用，新產生的學習歷程亦同樣納入研究範圍。 這是研究規模「持續增加」的來源——並非回溯性資料本身在變動，而是新資料不斷加入。 After IRB approval, the platform continues to operate and students continue to use it; newly generated learning records are likewise included in the research scope. The growing dataset reflects new additions, not modifications to the retrospective data.
無論是回溯性或前瞻性資料，使用前一律先經 Uedu Lab 去識別化處理。 您可於任何時間至個人設定撤回研究同意， 系統將自動把您的資料（包含過去已累積與未來新產生的）從後續研究匯出中排除。 Whether retrospective or prospective, all data undergo Uedu Lab de-identification before use. You may withdraw research consent at any time via account settings; the system then excludes all of your data — both accumulated and future — from subsequent research exports.
作為平台使用者，您對自己的資料享有以下權利。 行使任何一項權利都不會影響您使用平台的權益與課程成績。 As a platform user, you hold the following rights over your own data. Exercising any of these rights never affects your platform access or course grades.
如需簽署或重新閱覽各類同意書，可由下方進入。 Sign or review any of the following consent forms and policies below.
我們歡迎您與計畫主持人直接討論，或向機構倫理委員會反映意見。 您的每一次詢問，都是幫助平台做得更透明、更值得信賴的動力。 We welcome direct conversations with the PI and feedback to the reviewing IRB. Every question helps us make the platform more transparent and trustworthy.
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