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    Title: A design of English learning target recommender mechanism
    Other Titles: 英語學習標的推薦機制設計
    Authors: 季振忠;Chi, Chen-Chung
    Contributors: 淡江大學資訊工程學系博士班
    郭經華
    Keywords: 餘弦相似度;文章推薦系統;文件可讀性;Cosine similarity;Article recommender system;Document readability
    Date: 2015
    Issue Date: 2016-01-22 15:03:44 (UTC+8)
    Abstract: 對於許多以英語為第二學習語言的學習者而言,藉由閱讀英文文章或聽英文歌曲,不失為可以精通英語閱讀與聽力的語言學習方法。然而,在學習的過程中,總是要經過許多次的嘗試,才能找到既符合自己的興趣,又能符合自己英語字彙能力的歌曲或英文文章等學習標的。
    有鑑於目前「數位原生世代」學習者,相較於「數位原生世代」學習者,更愛用3 C(電腦、通訊、消費型電子)產品與社群網路服務的特性,本研究所設計的學習標的推薦系統,為了要迎合這些數位原生世代學習者的學習需求,亦結合YouTube與Facebook等強大的社群網路服務,並引入IWill這個以高中生為主的英語學習平台中的學習者資料,以學習者語料庫分群的機制,嘗試分析這個學習族群的字彙能力,據以提供更精確的推薦。
    本論文分為二大部分:其一為設計一套機制,基於高中生的字彙能力,辨識英語學習標的的字彙難度,據以選擇並推薦合適的英語標的供學習者學習,經本研究實驗證實這套機制中的字彙難度篩選機制,可以明確的區分學習者寫作文章、台灣高中英語課文與英文新聞文章之間的字彙難度差異;其二為應用字彙難度辨識機制,推薦字彙難度合宜的歌曲,以行動學習或以網頁形式,讓學習者在聽歌的同時,藉由閱讀歌詞與選擇正確搭配字的形式,著重於動詞-名詞的搭配字學習,透過計算互斥資訊的方法,以分辨語料庫中的正確或錯誤的搭配字,在行動載具或電腦上,隨時隨地在行動裝置上提供聽力與搭配字使用能力的練習管道。
    For many EFL (English as Foreign Language) learners, reading English articles or listening to music has always been a good way to improve their English proficiency. However, it’s always not easy to find appropriate learning target for fulfill learners’ interest and vocabulary ability.
    Nowadays most learners are “digital natives.” Compared to the characteristics the “digital immigrants”, the “digital natives” are used to using 3C (computers, communications, and consumers) products. Therefore this approach tries to develop a learning target recommender system that combine powerful social network – Youtube and Facebook, and import learner corpus – IWill (an English learners’ learning platform), tries to clustering the vocabulary characteristic this corpus to find out learners’ vocabulary using trend, therefore recommend appropriate learning target for learners.
    Two parts have been implemented in this approach. The first part is to describe the vocabulary difficulty filtering mechanism, and then use it to choose and recommend appropriate learning target for English learners; The second part is applied this mechanism to recommend music video via mobile device or web browser, the design of the proposed recommend system has focused on the study of correlation word of Verb-Noun, let learners can learning by watch dynamic displaying lyrics sentence by sentence, and listen music audio at the same time; This proposed system fetching worth learning collocation words by calculating mutual information of corpus, and then provide a practice tool for improve both reading and listening skill.
    Appears in Collections:[資訊工程學系暨研究所] 學位論文

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