本案例依原書 4.7「Education Case Study: By Khan Academy」整理。
理解 AI-enabled Learning System 如何依 Learner Strength／Weakness 調整 Course／Skill Challenge。
原書指出 Khan Academy 有 AI-based Learning System，可透過 Mastery Challenges 辨識 Learner Strengths／Weaknesses，並提高或降低 Course Overall Challenge 或不同 Skill Level。
| 面向 | 原書內容 | 教學用途 |
|---|---|---|
| 平台 | Khan Academy | Education Case Study |
| Signal | Mastery Challenges | 辨識 Strength／Weakness |
| Adaptation 1 | Overall Course Challenge | Increase／Decrease Difficulty |
| Adaptation 2 | Individual Skill Levels | Personalized Learning |
| Learning Gain | 原書未提供 | 不可補 Score Improvement% |
Excel 可記錄 Skill、Attempt、Mastery Level、Difficulty Adjustment、Post-assessment；AI 可協助個人化建議，但需用 Learning Outcome 驗證。
原書沒有 Student Count、Score Gain、Completion Rate 或 Engagement Improvement。
Adaptive Difficulty 是一種教學機制，不等於已證明學生學習成效提高多少；評估仍需 Learning Outcome Data。
請依 Learner Skill、Mastery Evidence、Difficulty、Next Task 建立 Adaptive Learning 表；若沒有前後測數據，不要宣稱成效提升。