學習分析在學習管理系統上的應用

In the past, students learning behaviors were significantly untrackable and mentor/mentee apprenticeship was the only method of creating accurate and individualized instructional interventions. But nowadays, huge amounts of the tracking data is available from the learning management system (LMS) and leads to the importance of using analytics by the recognition of government stakeholders, legislators, education professionals, research institutes, and service providers. This course is designed for graduate students who have little or no previous exposure to Academic Analytics and/or Learning Analytics. After a successful completion of this course, students will be able to: 1. Understand the demands of Learning Analytics at higher education institutions. 2. Identify major methods and examples of Learning Analytics. 3. Develop creativity and usability of data visualization. 4. Judge the quality of Learning Analytics research. 5. Criticize ethical issues in data-driven research such as Learning Analytics. 6. Be motivated to pursue advanced degrees and careers in the new field of educational data sciences. (The instructor will also model how a synchronous and asynchronous online course is taught)

課程目標: 受到企業界透過大數據(Big-Data)分析消費者行為的趨勢影響,透過大學手上長期蒐集卻尚未妥善利用的大數據,追蹤分析即時的學生樣貌,並據此研擬適當的教學診斷或學習支援方案,成為教育學界可供探討的新方向。學生在修完本課程之後,應該具有下列知能: 1. 瞭解大學院校對於學生學習歷程資料的分析需求; 2. 認識學習分析領域常用的實例與方法; 3. 發展資料視覺化的創意,提升分析結果的易使性(usability); 4. 批判資料導向研究可能衍生的倫理問題; 5. 判斷學習分析相關研究的品質; 6. 培養修課同學朝教育資料科學(educational data science)等進階學位進修的興趣。 (本課授課教師會以本課程內容示範同步與非同步線上教學之進行)

1. 自106-2 開始使用 Moodleset http://140.113.41.28/ 2. 如果要選課的同學,記得把 Moodleset 上的聯絡方式變更為 gmail or g-suite 信箱。

Canvas Instructure will be used as the LMS for this course. Click for the Syllabus https://docs.google.com/document/d/11Z89E1ARiSYuLgjjKwuT_MtDIidwRR7l5v_wDKKm98A/edit?usp=sharing 點選打開課程大綱 https://docs.google.com/document/d/11Z89E1ARiSYuLgjjKwuT_MtDIidwRR7l5v_wDKKm98A/edit?usp=sharing

時間

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