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研究生: 陳秀惠
Hsiu Hui Chen
論文名稱: 運動學習曲線理論之建構--動力系統觀點
construactinn a theory of motor learning curves- dynamical system approach
指導教授: 林清和
Lin, Ching-Ho
劉有德
Liu, Yeou-Teh
學位類別: 博士
Doctor
系所名稱: 體育學系
Department of Physical Education
論文出版年: 2002
畢業學年度: 90
語文別: 英文
論文頁數: 130
中文關鍵詞: 學習曲線多肢段運動
英文關鍵詞: learning curve, movement time, movement smoothness, movement pattern, learning function, multi segments
論文種類: 學術論文
相關次數: 點閱:196下載:47
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  • An Abstract of The Thesis of
    Hsiu-Hui Chen for the degree of Doctor of Philosophy presented on May 30,2002. Title: Constructing the Theory of Motor Learning Curves—Dynamical System Approach
    The process of learning two multi segments motor skills were examined as the basis to construct the theory of learning curve in dynamical system perspective. Four adults participated in experiment one learn the pedalor task for 350 trails in 7 individual days. An opto-electronic tracking system was used to record movement trajectories. The variability of movement velocity, movement time and different between two successive trials in space were derived as the temporal and spatial variables to assess the performance. The Cauchy theorem was applied as the criterion to quantify the learning process, and the exponential and power function were test for describing the learning behavior. Four junior high school students participated in experiment two to learning the virtual ball hitting task of 60 trials or 30 minutes a day for 12 individual days. A virtual reality simulation system was used to create the visual information for learning a forehand hit task. A movement image digitize system was used to capture the displacement in 2 dimension space and the differences of two successive trials were derived for analysis. The results of two experiments in this study showed that the exponential function is best for describing the multi segment motor tasks in this study. The study also provided an useful measure device for investigating the high dimensional system of motor learning. These findings provide the empirical evaluation for dynamical system theory for motor learning curve, and also extend our current knowledge on the process of multiple segments motor coordination.

    An Abstract of The Thesis of
    Hsiu-Hui Chen for the degree of Doctor of Philosophy presented on May 30,2002. Title: Constructing the Theory of Motor Learning Curves—Dynamical System Approach
    The process of learning two multi segments motor skills were examined as the basis to construct the theory of learning curve in dynamical system perspective. Four adults participated in experiment one learn the pedalor task for 350 trails in 7 individual days. An opto-electronic tracking system was used to record movement trajectories. The variability of movement velocity, movement time and different between two successive trials in space were derived as the temporal and spatial variables to assess the performance. The Cauchy theorem was applied as the criterion to quantify the learning process, and the exponential and power function were test for describing the learning behavior. Four junior high school students participated in experiment two to learning the virtual ball hitting task of 60 trials or 30 minutes a day for 12 individual days. A virtual reality simulation system was used to create the visual information for learning a forehand hit task. A movement image digitize system was used to capture the displacement in 2 dimension space and the differences of two successive trials were derived for analysis. The results of two experiments in this study showed that the exponential function is best for describing the multi segment motor tasks in this study. The study also provided an useful measure device for investigating the high dimensional system of motor learning. These findings provide the empirical evaluation for dynamical system theory for motor learning curve, and also extend our current knowledge on the process of multiple segments motor coordination.

    Table of Contents Chapter page 1. Introduction 1 Purpose of Study 4 Research Problem and Hypothesis 4 Delimitation 8 Operational Definition 8 Motor Learning Curve 8 Multi Segments 9 Learning Variable 9 Movement Pattern 10 Movement Time 10 Movement Smoothness 10 2. Review of Literature 11 Motor Learning Curves 11 The Definition of Motor Skill and the Way to Quantify 11 Traditional Perspective on Motor Learning Curve 13 Learning Theory and Learning Functions 15 Single Function? 19 Dynamical System Perspective of Motor Learning 23 Concept of Dynamical System Theory 23 Dynamic of Motor Learning 27 Time Scale as Feature of Motor Learning 28 Learning Function and Time Scale—How the Learning Functions Describe the Behavior? 30 Continuous Learning Behavior 30 Discrete Learning Behavior 36 3. Methods 39 Experiment One 39 Participants 42 Apparatus 42 Task 44 Procedure 44 Data Analyses 45 Experiment Two 48 Participants 49 Apparatus 50 Task 51 Procedure 52 Data Analyses 52 4. Results 54 Experiment One 54 Movement Pattern 54 Approaching Behavior 54 Curve Fitting 64 Movement Time 69 Approaching Behavior 69 Curve Fitting 78 Movement Smoothness 83 Experiment Two 91 5. Discussion 95 Experiment One 95 Learning Behavior 95 Quantify the Learning Process 98 Transitory Change 100 Experiment One 104 Change of Movement Pattern 104 6. General discussion 106 Reference 110 Appendix 117 List of Table Table page Table 2.1 35 Table 4.1 65 Table 4.2 66 Table 4.3 67 Table 4.4 68 Table 4.5 79 Table 4.6 80 Table 4.7 81 Table 4.8 82 Table 4.9 89 Table 4.10 90 Table 4.11 90 Table 4.12 94 Table 4.13 94 List of Figure Figure page Figure 2.1 31 Figure 2.2 32 Figure 2.3 34 Figure 2.4 35 Figure 2.5 37 Figure 2.6 38 Figure 3.1 42 Figure 3.2 43 Figure 3.3 51 Figure 4.1 56 Figure 4.2 57 Figure 4.3 58 Figure 4.4 59 Figure 4.5 60 Figure 4.6 61 List of Figure (continued)Figure page Figure 4.7 62 Figure 4.8 63 Figure 4.9 70 Figure 4.10 71 Figure 4.11 72 Figure 4.12 73 Figure 4.13 74 Figure 4.14 75 Figure 4.15 76 Figure 4.16 77 Figure 4.17 84 Figure 4.18 85 Figure 4.19 86 Figure 4.20 87 Figure 4.21 91 List of Figure (continued)Figure page Figure 4.22 92 Figure 4.23 93 Figure 5.1 103

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