教育部於108年公佈十二年國民基本教育課程綱，其中對於學生的自主學習有了全新的設計，期望學生能自行規劃學習目標、搜尋學習資源，而且更注重學生在學習過程中的狀態以及與同儕之間的交互關係。由於自主學習時往往需要融合跨領域的知識，很可能超出教師的能力範圍，所幸網路上的相關資源廣泛，可供參考，但使用搜尋引擎時可能因為查詢的結果相關性不足，或引用了不當資訊反而造成學習迷失；為使自主學習活動能順利進行，極需要具備權威性且有效的學習資源作為輔助支持。
本論文為此建立網路資源推薦系統，利用經專家篩選過之34191篇網路科普文章進行文字探勘建立字詞間的關聯矩陣，以輔助高中師生進行自主學習活動時搜尋相關的學習資源使用。推薦系統以雲端看板（Kanban）為使用者界面，支持學生進行自主學習時的資料蒐集及探索過程，預期能使學生更加方便理解自然科學理論與相關概念。研究分析以中學教師為對象蒐集問卷，包含正確性、相關性、總體表現與滿意度，分析結果發現系統對於學習者思維發散有所幫助。除教師問卷外也將搜尋結果與常用搜尋引擎相比，結果發現本論文提供之推薦系統之搜尋結果範圍較一般搜尋引擎的搜尋結果更加廣泛，並可有效提供連結相關知識之關鍵字，同時也發現推薦系統訓練集的數量會顯著影響查詢結果，建議未來發展以文字探勘為基礎之學習資源推薦系統相關研究可增加訓練文本或以演算法進行細部分類，以提高系統搜尋精確度與關聯度。

A brand new self-directed learning (SDL) course was designed by MOE in 2018 for high-school students, which expects students to plan their own learning goals, search for learning resources, and pay more attention to the learning process, meanwhile, interacting with peers. Since SDL needs to integrate cross-disciplinary knowledge, it is likely beyond the teacher's ability. Fortunately, there are many resources on the Internet that support SDL. However, these resources may be of low relevance or misinformation when using general search engines that students rely on.
This thesis establishes an online learning resource recommendation system, using 34,191 popular science articles screened by experts to develop an association matrix between words through text mining to assist high school teachers and students search for relevant learning resources. The recommendation system uses Kanban as the user interface to support the process of data collection and exploration. Students are expected to understand natural science theories and related concepts more quickly. The analysis of questionnaires from middle school teachers indicates that the system is helpful for learners to diverge. The results also show that the learning resources suggested by the system are more extensive than general search engines did. Future research is recommended to expand the training set or use different algorithms to improve the accuracy and relevance of learning resources for SDL.

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