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    Title: 影響高中學生學習表現之研究
    A Study of Affecting Learning Performance of Junior High School Students
    Authors: 張芃婕
    Contributors: 鄭宇庭
    張芃婕
    Keywords: 決策樹分析
    高中教育
    學習表現
    學習投入
    Decision tree analysis
    High school education
    Learning performance
    Learning engagement
    Date: 2018
    Issue Date: 2018-07-03 17:23:56 (UTC+8)
    Abstract: 本研究以103學年度全國高二普通科學生為分析對象，將學生特性歸類為行為學習投入、情緒學習投入、認知學習投入與人口統計變項。首先透過統計分析了解資料之特性，接續採用卡方檢定，以篩選重要之變項，而後再以分類決策樹模型，分別針對不同學習表現之學生建構其模型，以釐清各學習表現之學生特性。研究結果發現，高二學生之情緒學習投入與行為學習投入向度較為顯著；而高度學習表現之學生對學校課程感興趣程度有明顯的特性；中度學習表現之學生在課外閱讀、社團和運動方面，投入程度較為明顯；對於低度學習表現之學生，在課程感興趣程度及自我期許上，有其明顯特性。研究結果可提供高中教育教學實務之參考。
    This study analyzes the senior high students of general education in second grade in 2015 all over the country, and the variables of student characteristics are divided into behavioral engagement, emotional engagement, cognitive engagement, and demographic variables. First, the distribution of student characteristics, measured by this research definition, is used to realize the patterns of data. Choose the important variables by the Chi-square test. And then, use the decision tree analysis to construct three models of learning performance to clarify the student characteristics in different models. The results show that the dimensions of emotional engagement and behavioral engagement are more significant；For the students in high-end learning performance, the pattern of level interest for lessons in schools is obvious；The level of engagement on extracurricular reading, club, and exercise for the students in mid-level learning performance is significant.；For the students in low-end learning performance, the patterns of level interest for lessons in schools and self-expectations are obvious. The results of the study would provide some reference for teaching in senior high school.
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    Description: 碩士
    國立政治大學
    統計學系
    1043540111
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G1043540111
    Data Type: thesis
    DOI: 10.6814/THE.NCCU.STAT.003.2018.B03
    Appears in Collections:[Department of Statistics] Theses

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