適性化的使用者模組案例式學習知識庫; User Model Adaptive Case-Base Learning Library

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Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/8636

Title:	適性化的使用者模組案例式學習知識庫;User Model Adaptive Case-Base Learning Library
Authors:	鄭廉勳;Lian-Xun Zheng
Contributors:	資訊工程研究所
Keywords:	學生模組;案例式推理;案例式學習;概念構圖;適性化;Student Model;Case-based Learning;Concept Map;Case-Based Reasoning;Adaptive
Date:	2002-06-25
Issue Date:	2009-09-22 11:32:09 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	案例式學習(Case-Based Learning)在醫學、法律上已被廣泛的使用，程式設計的學習過程中，以程式範例為主的學習亦也是的案例式學習。藉由網路學習的日漸普及，網路學習日益受到重視，在大部分網路學習系統並未具有學生模組(Student Model)，這樣的網路學習環境，並不容易幫助教師掌握學生學習狀態與行為，缺乏學生模組的網路學習環境難以適時的提供針對學生個人適性化的(Adaptive)學習輔助。在本篇論文中，藉由『案例式學習』的學習架構，我們建構一『適性化的使用者模組案例式學習知識庫』來幫助學生學習程式設計，『案例式學習知識庫』內的案例內容包含：大一 Java 程式設計課程的程式範例、學生修課時的程式投稿與學生所繳交的作業，我們將所收集的程式案例利用案例式推理(Case-Based Reasoning)作案例的概念分析，使案例與學習程式設計的概念構圖(Concept Map)建立關聯。藉由以案例為基礎的知識表示架構，可幫助研究者更準確的獲取學生學習時的學生模組(Student Model)，瞭解與預測學生即時的學習狀態，以針對學生的學習狀態產生一適性化(Adaptive)的『智慧學習引導』與『概念學習引導』，幫助學生快速掌握學習重點縮短學習時間提高學習新知識的學習成效。 User Model Adaptive Case-Based Learning Library is constructed based on Case-Based Learning, to help student to learning programming. Case-Based Learning widespread be used in medical and law. In programming, learning is based on ‘program-example’, is also a Case-Based Learning. In many Network-Based learning system without consider student model. A learning environment without student model, that is not easy to help teacher to understand student’s learning status and behavior. This kind of learning environment can’t give student personalize and adaptive learning assistance. ‘Program-example’ in Case-Base Learning Library include program example of textbook and student’s portfolio and publish in web journal. All these materials are transforming to the representation of knowledge of Case-Base Learning Library. And make the relation with case and concept of concept map by Case-Based Reasoning. The representation of knowledge of Case-Based Learning Library can help researcher build more accurate student model to understand and predict student’s learning status and behavior.
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] Electronic Thesis & Dissertation

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