本計畫應用巨量資料(Big data)，透過學習管理系統(包含NCUx 中央大學磨課師與Maple TA 兩大學習管理系統)與校務行政系統蒐集學生學習歷程，以學習分析(learning analytics)為研 究主軸來發展學習分析系統，教師可依據學習分析系統的分析結果，適時對各種學生族群提 出適當有效的學習策略建議與學習輔導。應用巨量資料技術發展學習分析機制，探討學習者 的學習行為型態、學習行為與成績的關聯性、以及影響學習者投入程度(engagement)及提升學 習成效的關鍵因素，並探討如何提供這些關鍵因素做為教師輔導策略以及學習者自我監控的 參考依據。上述這些重要的研究議題，也將成為推動MOOCs 的重要關鍵。 本計畫所發展學習分析系統包含學習成效預測模型、學習分析模型、學習行為視覺化模 型等三大模型。學習成效預測模型主要透過機器學習演算方法，找到學習成效不佳之學生， 及時給予適當的輔導補救；學習分析模型將透過統計分析理論方法，探討分析學生學習行為 與成績的關聯性，以及分析造成學生獲得該成績的關鍵學習行為，做為教師介入輔導的輔導 策略參考依據；學習行為視覺化模型將提供視覺化界面給教師，視覺化介面包含學習分析系 統與影片瀏覽行為的視覺化圖形，輔助教師根據學習者影片瀏覽行為的視覺化分析圖形，針 對影片學習內容進行修改與調整，並讓教師可根據學習分析系統的視覺化圖形，提供學生學 習成效預測情況，以及各學生族群之學習策略建議，做為教師介入輔導的參考依據，達到提 升學習成效的目標。 ;This study applying big data to develop learning analytics system by using the huge collected learners’ learning portfolio data in the NCUx MOOCs and Maple TA learning management systems and the school administration system. According to the analytics results, teachers can provide remedial activity based on effective learning strategy suggestions. Applying Big data to develop learning analytics mechanism can explore the learners’ learning behaviors, the relationships with learning behaviors and learning outcome, the critical factors for influencing the engagement degree, and further, finding the critical factors for promoting learners’ learning outcome. Can these critical factors be considered as the reference information for the teachers’ remedial strategy and learners’ self-monitor? For the above researching subjects, they have been become the main power for promoting MOOCs. The proposed learning analytics system consist of learning outcome prediction, learning analytics, and learning behaviors visualization models. The main goal of the proposed learning outcome model based on machine learning algorithms is to find at-risk students to give suitable remedial activity. Providing the reference information for the teachers’ remedial strategy, the learning analytics model based on statistical analysis theory aims to explore the relationships between learners’ learning behaviors and learning outcome, and investigate the learners’ critical learning behaviors causing their learning outcomes. Learning behaviors visualization model consist of visualization graphs of learning analytics system and learners’ viewing videos behaviors. According to the visualization graphs of learners’ viewing videos behaviors, teachers can modify the videos learning content to improve the quality of videos. To improve learning outcome, teachers give remedial learning activity based on the learning strategies for the predicted learning outcome groups.
