臺灣博碩士論文加值系統

全球資訊網越來越普遍，許多遠距教學系統都建構於全球資訊網上，讓學生能夠更方便地透過網路進行學習。在傳統的實體教室，老師必須透過書面的記錄來觀察學生的學習過程，並以觀察到的現象來改善教學方式。網路教學系統被設計來記錄學生行為，並提供老師評量輔助與決策，然而一般的網路教學系統雖能將學生的學習行為記錄在網站日誌中，但這些日誌並沒有專為教育上的目的來設計。許多網站日誌的分析工具亦不能滿足老師的需求，主要的困難在於老師無法從網站日誌中看出教育上的意義，或是找出學生學習行為模式以調整教學策略。在本論文中，我們引進決策樹技術、data cube與分群的方法來輔助老師觀察、決策與評量，並且說明了這些技術在教育上的使用，老師能夠線上找出決策規則，根據這些規則老師可以評估並制定教學策略，而透過決策樹與data cube老師也能調整教學的方式。

As World Wide Web becomes increasing popular, many distance learning system are constructed on the web to enable students conveniently learning on the Internet. In conventional classrooms, teachers monitor students’ learning processes by paper records and utilize observed phenomenon to improve instruction. Hence, distance learning systems are designed to record students’ behaviors to assist teachers in performance assessment and decision making. Recently, a general, without specifically design, web based learning system can record students’ access to the learning system in web logs. However, these logs are not designed and maintained for pedagogical purpose. Current analysis instruments for the logs can not satisfy the requirement of teachers. The primary obstacles are that the teachers can not easily infer the pedagogical meaning of web logs and discover the potential rules of students’ behavior patterns in the web logs to refine teaching strategies. Hence, this paper proposes decision tree and data cube methodologies to observe students’ behaviors and discover the potential rules in the web logs. The architecture and guideline for utilizing the data cube and decision tree methodologies in pedagogical purpose is depicted. Consequently, teachers can online and efficiently discover potential decision rules in the web logs for estimating and explaining the effectiveness of teaching strategies and improving instruction with decision tree and data cube software.

第一章.緒論1
1.1背景1
1.2動機2
1.3問題3
1.4目標4
1.5論文架構5
第二章.An IBIS 討論範例6
第三章.使用資料庫與決策樹技術的理由10
3.1行為觀察10
3.2重新組織網頁日誌10
3.3行為記錄上的多維觀點12
3.4決策樹分析17
第四章.分群輔助25
4.1程式作業的分群26
4.2架構值的計算27
系統架構與實作29
5.1學習記錄的資料庫綱目31
5.2data cube的建立33
5.3決策樹軟體程式的使用35
5.4AutoClass操作細節36
第六章.結論38
參考文獻39

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