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研究生：	邱瓊芳
論文名稱：	以教學影片及實驗策略進行影像處理原理學習之研究 Learning of Image Processing Concepts in High Schools: A Lecture Video and Lab-based Approach
指導教授：	李忠謀 Lee, Chung-Mou
學位類別：	博士 Doctor
系所名稱：	資訊教育研究所 Graduate Institute of Information and Computer Education
論文出版年：	2009
畢業學年度：	97
語文別：	英文
論文頁數：	127
中文關鍵詞：	實驗策略、影像處理、模擬軟體
英文關鍵詞：	lab-based approach, image processing, simulations
論文種類：	學術論文
相關次數：	點閱：417 下載：8
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本研究提出整合教學影片及實驗策略之學習模式進行高中影像處理原理之學習。研究採準實驗研究法，比較此學習模式對學生學習影像處理之學習成就、對學習活動看法、以及學習電腦科學原理興趣之差異。此外，亦探討學習者特質對課前瀏覽教學影片之影響。研究參與者為二所高中各六個班級的學生，其中兩班學生為實驗組1，兩班學生為實驗組2，另兩班學生為控制組（採用傳統講述法）。實驗組1學生於課前瀏覽教學影片，課堂上進行實驗活動；實驗組2學生於課堂先接受影像處理原理教學，再進行實驗活動;控制組學生則於課堂接受影像處理原理教學。研究結果發現：(1)整合教學影片及實驗策略是可行及有效學習影像處理原理之學習模式；(2)此學習模式可促進課堂上同儕之間及師生之間的互動；(3) 此學習模式可提升學生對學習電腦科學原理之興趣；(4)學生特質方面，學習動機是課前瀏覽教學影片的重要因素。

This study proposed a hybrid lecture video plus lab approach for learning of image processing concepts in high schools. The effects of this learning model upon students’ performance and attitudes were investigated. Furthermore, the relationship between learners’ characteristics and before-class video viewing behaviour was also explored. A quasi-experimental research design was conducted at two high schools to examine the results. Six classes were randomly chosen for the experiment from each school. Of the six classes, two classes each were designated as experimental group 1, experimental group 2, and the control group. Students in the experimental group 1 (video+lab group) watched lecture videos before class and used the class time for lab exercises. Students in the experimental group 2 (lecture+lab group) received in-class lectures (the same content as in the lecture videos) and carried out lab exercises in class. The control group received the usual expanded lectures in class. The experimental results show that the proposed model is a feasible and effective way for the teaching and learning of image processing. The new approach also facilitates student-student and student-teacher interactions in the classroom. An improvement in the understanding of the subject by the students and an increased interest toward learning CS are also evident. Furthermore, students’ learning motivation is an important factor for before-class video viewing.

Contents

List of Tables    III
List of Figures    IV
Chapter 1  Introduction    1
1.1 Statements of the Problem    3
1.2 Statements of the Purpose    4
1.3 Research Questions    5
1.4 Research Limitation    5
1.5 Organization of Thesis    5
Chapter 2  Literature Review    7
2.1 Use of Video Technology to Deliver Learning Content    7
2.2 Use of Video Technology as a Learning Tool    12
2.2.1 Recording Tool    12
2.2.2 Context Presentation Tool    17
2.2.3 Authoring Tool    20
2.3 Lab-based Learning    21
2.4 Image Processing Teaching    23
2.5 Learners’ Characteristics    29
Chapter 3 Research Methodology    33
3.1 Research Design    33
3.2 Participants    33
3.3 Procedure    34
3.4 Research Tools    37
3.4.1 Lecture Video    37
3.4.2 Course Supporting Website    39
3.4.3 Instruments    41
3.4.4 Achievement Test    42
3.5 The IP Lab Pack    42
Chapter 4  Research Results and Discussions    49
4.1 Video Viewing Statistics    49
4.2 Achievement Test Analysis    50
4.2.1 Achievement Test Analysis among the Video+Lab, the Lecture+Lab, and the Control Groups    50
4.2.2 Achievement Analysis within the Video+Lab Groups    54
4.3 Characteristics of video users and nonusers    58
4.3.1 Mastery Goals and Performance Goals    58
4.3.2 Application-specific Self-efficacy    62
4.3.3 Internet Access    64
4.4 Student Questionnaire    65
4.5 Teacher Interviews    75
4.6 Summary Findings    79
Chapter 5 Conclusions and Future Works    81
5.1 Conclusions    81
5.2 Future Works    82
REFERENCE    84
APPENDIX A.  Questionnaire of learners’ characteristics.    97
APPENDIX B.  Questionnaire for video+lab group.    98
APPENDIX C.  Questionnaire for lecture+lab group.    100
APPENDIX D.  Post-achievement test.    101
APPENDIX E.  Worksheet used in week 1.    105
APPENDIX F.  Worksheet used in week 2.    109
APPENDIX G.  Worksheet used in week 3.    114
APPENDIX H.  Teaching notes used in week 1.    116
APPENDIX I.  Teaching notes used in week 2.    120
APPENDIX J.  Teaching notes used in week 3.    124

List of Tables
Table 3.1 Number of students participated in the study.    34
Table 3.2. The time duration of the learning activities for each of the three groups.    37
Table 3.3. Topics covered each week.    38
Table. 4.1. Descriptive statistics of the achievement-test scores in two schools: (a) school A. (b) school B.    53
Table 4.2. The results of multiple posterior comparison (mean difference and p-value)  of the three groups in (a) school A and (b) school B.    55
Table 4.3. Descriptive statistics of the achievement-test scores of the video+lab group at the two schools. (a)school A. (b) school B.    56
Table 4.4. ANCOVA analysis (mean difference and p-value) of the achievement test scores among the three subgroups of the video+lab group. (a) school A. (b) school B.    57
Table 4.5.  Students’ responses of mastery goals questions.    60
Table 4.6.  Students’ responses of performance goals questions.    61
Table 4.7. T-test for equality of means on mastery goals in school A and school B.    62
Table 4.8. T-test for equality of means on performance goals in school A and  school B.    62
Table 4.9.  Students’ responses of application-specific self-efficacy questions.    63
Table 4.10. T-test for equality of means on application-specific self-efficacy in school A and school B.    64
Table 4.11.  Students’ responses on Internet access question.    64
Table 4.12. T-test for equality of means on Internet access in school A and school B.    65
Table 4.13. Student questionnaire and its results in video+lab group.    71
Table 4.14. Student questionnaire and its results in lecture+lab group.    73
List of Figures
Figure 3.1.  The teaching experiment procedure.    36
Figure 3.2.  The architecture of the course supporting website.    39
Figure 3.3.  Snapshot of the course website.    40
Figure 3.4.  Snapshot of handwritten numeral feature extraction tool (DIPFeature).    45
Figure 3.5.  Snapshot of handwritten numeral cognition tool (DIPLab).    48
Figure 3.6.  Sn6apshot of setting up the threshold for feature extraction.    48
Figure 4.1.  (a) Percentage of students in the video+lab group that have viewed lecture videos before class. (b) Percentage of students in the video+lab group that have viewed lecture videos before class only once in one, two or all three weeks.    52
                                

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