淡江大學機構典藏:Item 987654321/87932
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/87932


    Title: 智慧型歌曲學習推薦 : 依學習者的族群與習慣
    Other Titles: Smart language learning tool via lyrics : according to learner groups and habits
    Authors: 賴彥均;Lai, Yen-Chun
    Contributors: 淡江大學資訊工程學系碩士在職專班
    郭經華;Kuo, Ching-hua
    Keywords: 歌詞;行動學習;網路服務;相互資訊;搭配詞;推薦系統;Lyrics;Mobile Learning;Web Service;Mutual Information;Collocation;Recommendation System
    Date: 2012
    Issue Date: 2013-04-13 11:52:55 (UTC+8)
    Abstract: 　　本論文主要是從歌曲歌詞的生動活潑方式來進行學習英語的工具，藉由社群網路的方式來取得學習者的資訊及網站上的習慣操作來推薦其學習者學習歌曲的曲目，並經由學習者選擇的學習方式來進行顯性與隱性的回饋，使得本研究的學習機制會不斷的自我學習並修正，再依照各學習者的不同引發出個學習者專屬的學習方式。
    　　研究內容會著重在自動學習成長的引擎機制，最主要的兩大主要方向-顯性回饋、隱性回饋。顯性回饋-會依照學習者選擇的難易度對某首歌曲歌詞作適當的單字及片語拆解。隱性回饋-會依照使用者的資訊及在此系統上的操作方法與喜好來做分類。因應國內網路使用者的習慣跟習性不一定會接受顯性的學習方式，所採取主動式的收集學習者喜好來改變被動式學習所缺少的因素。
    　　此研究中，使用英國國家標準語料庫及目前國內所使用的全民英檢的字彙來當作系統的與料庫來源，並透過交叉資訊運算將每首歌曲歌詞劃分為不同等級的字彙學習，並篩選出目前最常使用的片語及單字來作為翻譯或遊戲的基礎，因系統採用Web2.0的方式來設計，在對於目前國內眾多作業系統及智慧型手機系統，有著跨平台及統一的特性。
    This paper is mainly about using lyrics as an English learning tool, making it more creative and vivid. The songs are selected based on the learners’ info from a social network & their behavior on the website. A learning
    mechanism is designed by using explicit & implicit feedback from the learner’s behavior on the website. As a result, the learning mechanism will improve itself and adjust continuously to fit the learner’s needs.
    The research focuses on the self-learning mechanism. Since users do not always respond to explicit feedback during their learning process, the website collects the learner’s preferences in order to minimize disadvantages with passive learning.
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Thesis

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