COVID-19疫情加速了數位學習平台的普及與使用。但對於學生在數位學習平台上的學習行為，多數的評量仍聚焦於學生的學習產出，但對於學習歷程中的資訊，則較少被關注。本課程主要介紹目前常見的數位學習平台（例如因材網、均一平台、TronClass課程平台），並探討如何從平台所記錄的學習行為資料檔來評量學生學習歷程與學習成效。
完成課程後，學生將能夠使用教育資料探勘技術演算法分析數位學習平台的學習軌跡資料，也能識別出數位學習過程中學生的學習行為模式並分析其特徵，並從數位學習平台的學習軌跡分析現有教育問題、教學模式或策略的缺點。

The COVID-19 epidemic has accelerated the popularity and use of digital learning platforms. However, most evaluations of students' learning behavior on digital learning platforms still focus on students' learning output, but less attention is paid to the information in the learning process. This course mainly introduces the currently common digital learning platforms (such as Yincai.com, Junyi Platform, and TronClass course platform), and discusses how to evaluate students' learning process and learning effectiveness from the learning behavior data files recorded by the platforms.
After completing the course, students will be able to use educational data mining technology algorithms to analyze the learning trajectory data of digital learning platforms. They will also be able to identify students' learning behavior patterns in the digital learning process and analyze their characteristics, and analyze the shortcomings of existing educational issues, teaching models or strategies from the learning trajectories of digital learning platforms.

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