TIMSS 2015臺灣資料中學生變項與數學成就之關聯：學習分析取向

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陳珈鈞(Jia-Jyun Chen) 查詢紙本館藏

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學習與教學研究所

論文名稱

TIMSS 2015臺灣資料中學生變項與數學成就之關聯：學習分析取向
(Relationship between Student Variables and Mathematics Achievement from TIMSS 2015 Data in Taiwan: Learning Analytical Approach)

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摘要(中)

數學是科學之母，說明數學的重要性。從定期參加的國際大型成就評量可知，臺灣學生數學平均成就高，但學生數學成就落差越來越大，是我們嚴重的教育問題。了解哪些變項使得學生獲得高數學成就變得相當重要。故本研究旨在使用TIMSS 2015資料庫中的數據資料，對學生在TIMSS 2015數學成就中的高成就組與低學習組進行分類。該研究樣本由參加2015年TIMSS的5711名臺灣八年級學生組成。在數據分析中，以決策樹DT、分類與回歸樹CART、支持向量機SVMs，三種資料探勘方法進行分類學生數學成就，再以Weka軟體常用適切度評估分類性能。從這三種資料探勘的方式找到最適合用於分類學生TIMSS 2015數學成就的方式是分類與回歸樹CART。透過分類與回歸樹CART獲得高成就組學生共同特徵有「數學學習自信」與「家庭教育資源」這兩項。日後可以進一步的研究和應用在參與TIMSS的各個國家上，TIMSS研究不僅涉及數學成績，還評估學生的科學和閱讀技能。因此，可以對不同的教育領域進行研究，以找出與課程成績相關的因素。

摘要(英)

Mathematics is the mother of science, which illustrates the importance of mathematics. From the regular international large-scale achievement assessments, we can see that the average achievement of Taiwanese students in mathematics is high, but the gap in mathematics achievement of students is increasing. This is a serious education problem for us. It is very important to understand which variables make students achieve high mathematics achievement. Therefore, this research aims to use the data in the TIMSS 2015 database to classify the high-achievement group and low-learning group of students in TIMSS 2015 mathematics achievement. The study sample consisted of 5711 Taiwanese eighth grade students who participated in the 2015 TIMSS. In the data analysis, three data exploration methods including Decision Tree, Classification and regression tree, and Support Vector Machines are used to classify students′ mathematical achievements, and then the classification performance is evaluated appropriately by Weka software. From these three data exploration methods, the most suitable method for classifying students′ TIMSS 2015 mathematics achievements is Classification and regression tree. Through Classification and regression tree, the common characteristics of high-achievement students are "Students Confident in Mathematics" and "Home Educational Resources". In the future, it can be further researched and applied in various countries participating in TIMSS. TIMSS research not only involves mathematics performance, but also evaluates students′ science and reading skills. Therefore, different education fields can be studied to find out the factors related to course performance.

關鍵字(中)

★ TIMSS
★ 數學成就
★ 教育資料探勘EDM
★ 數學學習自信
★ 家庭教育資源

關鍵字(英)

★ TIMSS
★ mathematics achievement
★ educational data mining（EDM）
★ students confident in mathematics
★ home educational resources

論文目次

目錄
中文摘要 i
英文摘要 ii
謝誌 iii
目錄 iv
圖目錄 vi
表目錄 vii
一、緒論 1
1-1 研究動機 1
1-2 研究問題 3
1-3 研究限制 4
1-4 主要名詞釋義 4
二、文獻探討 6
2-1 資料探勘 6
2-1-1 檢驗方式 7
2-2 資料探勘用於教育 10
2-2-1 決策樹（DT） 11
2-2-2 分類與回歸樹（CART） 11
2-2-3 支持向量機（SVMs） 12
2-2-4 十倍交叉驗證方法 12
2-3 國際大型資料庫與數學成就 13
2-4 教育資料探勘結合國際大型資料庫的研究 14
三、研究方法 18
3-1 研究設計 18
3-2 研究對象 19
3-3 研究工具 19
3-4 資料蒐集方法 23
3-5 資料分析方法 24
四、研究結果與分析 29
4-1 臺灣八年級學生變項與數學成就之敘述統計 29
4-1-1 學生變項與數學成就分群人數及百分比 29
4-1-2 高成就組與低學習組在七個變項中的平均分數 30
4-2 三種WEKA軟體分類性能之適切度分析 31
4-3 資料探勘分類結果分析 35
4-3-1 決策樹DT分類結果 35
4-3-2 分類與回歸樹CART分類結果 36
4-3-3 支持向量機SVMs分類結果 36
五、討論與結論 38
5-1 研究結果討論 38
5-1-1 資料探勘適切度評估分類性能 38
5-1-2 學生變項與數學成就之關係 38
5-1-3 方法學之突破與建議 39
5-2 結論與建議 40
5-2-1 本研究之結論 40
5-2-2 建議 41
5-2-3 研究總結與本研究之重要性 42
參考文獻 44

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指導教授

張立杰(Li-Chieh Chang)

審核日期

2021-8-23

推文