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研究生:廖文偉
研究生(外文):Liao,Wen-Wei
論文名稱:應用影像處理技術之虛擬題庫設計
論文名稱(外文):Design a Virtual Item Bank Based on Image Processing Technique
指導教授:何榮桂何榮桂引用關係
指導教授(外文):Rong-Grey,Ho
學位類別:碩士
校院名稱:國立臺灣師範大學
系所名稱:資訊教育研究所
學門:教育學門
學類:專業科目教育學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:68
中文關鍵詞:虛擬題庫影像處理試題曝光率
外文關鍵詞:Virtual Item BankImage ProcessingItem exposure
相關次數:
  • 被引用被引用:3
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摘要
應用影像處理技術之虛擬題庫設計
智力測驗起源於十九世紀末,當時有兩位學者Francis Galton和Mckeen Cattell對人與人之間的差異進行了各種行為方面的研究,如:記憶力、反應速度…等。雖然在當時並沒有重大的成就,但是卻為後來的智力測驗留下了許多有用的工具,及研究方法。
智力測驗分為文字及非文字測驗兩種,一般皆不公開,一般人對智力測驗的瞭解也只侷限於坊間書局所出版的智力測驗題庫、練習題本。不公開之主要原因在於維持測驗的的準確性。在非文字測驗中之圖形測驗,由於其編製費時,其保密之程度更高。另外由於非文字測驗之題庫通常皆不大,試題曝光率之問題也較為嚴重。在本研究中,將試著結合影像處理的技術,建立一套圖形化測驗命題系統。此命題系統將不再有傳統題庫的存在,取而代之的是一虛擬題庫。在虛擬題庫中,資料庫將只有基本的圖形原件(圓形、多邊型及直線)及將解題所需之能力、歷程轉換後之數學方程式。而在測驗當中,測驗受試者之題目,將由這些原件配合影像處理技術直接產生,題庫將不再有試題曝光率之問題。
The concept of Intelligence Quotient (IQ) test should be tested began with two nineteenth-century scientist, Francis Galton and Mckeen Cattell. They developed some important method to discover the relationship between heredity and human ability.
Item exposure of figural items in IQ test have become a more important question. In this paper. We propose the representation of Virtual Item Bank.Using the geometric class definitions of line segment,triangle,circle etc,image procseeing theory and Computerized adaptive testing (CAT) to generate and check the content of item. This concept solving the problem of item exposure and make it easily to develop a test.
Computer science has become increasingly important. In this paper we propsed a new approach and design a useful test tool that combines image processing theory and concept of figural test. This tool can improved traditional figural test successfully.
TABLE OF CONTENTS
CHAPTER 1 INTRODUCTION…………………………………………… 1
1.1 Purposes..………………………………………………………………. 3
1.2 Limitations……………………………………………………………… 3
CHAPTER 2 LITERATURE REVIEW……………………………………. 5
2.1 Computer Adaptive Testing…….………………………………….…… 5
2.1.1 Start Point and Ending Point..………..………………………….. 6
2.1.2 Ability Estimation and Item Selection…………………………… 7
2.2 Computer Figural Testing……………………………………………….. 9
2.2.1 Computerization of Traditional Mental Tests…………………… 9
2.2.2 New Figure Reasoning Test…………..……………………..…… 10
2.3 Image Processing Theory……...………………………………………... 15
2.3.1 Binary Operations.……………………………………………….. 15
2.3.2 Content-Based Image Retrieval.……………...………………….. 17
2.3.3 Method of Size Variation………………………………………... 19
2.4 Problem of Item Exposure Rate………………………………………… 21
CHAPTER 3 METHODS…………………………………………………… 22
3.1 Problems and Demand of Item Bank Generation……………..………… 22
3.2 Development of Research Tool.………………………………………… 25
3.2.1 Design Framework……………………………………………….. 25
3.2.2 System Development Environment…………...…………………. 26
3.2.3 System Structure……………………………………..…………... 26
3.2.3.1 Virtual Item Bank System……..……………………… 26
3.2.3.2 CAT System…….……………………………………… 34
3.2.4 System Algorithm………………………...………………………. 35
3.2.5 System Functions………………………………………………… 37
TABLE OF CONTENTS
CHAPTER 4 RESULTS AND DISCUSSION……………………………… 41
4.1 Item Rule Definition…………………………………………………….. 41
4.2 Parameter Estimation……….………………………………………….. 41
4.3 Item Overlap Simulation…………….………………………………….. 44
CHAPTER 5 CONCLUSION AND SUGGESTION……………………… 45
5.1 Conclusion……………………………………………………………… 48
5.2 Future Work…...………………………………………………………… 49
BIBLIOGRAPHY……………………………………………………………. 50
APPENDIX……………………………………………………………………. 52
A. The results of parameter-estimation……………..………………………. 53
B. Scale Statistics of parameter-estimation……………..………………….. 54
C. Items generated by Rule 1-48……..…………………………………….. 56
D. Items of three different Item Generation Rules………………………….. 64
Wainer, H., Neil J. Dorans, Ronald Flaugher, Bert F. Green, Robert J. Mislevy, Lynne Swteinberg, & David Thissen (1990). Computerized adaptive testing: A primer. Hillsdale, N.J.:Lawrence Erlbaum Associates.
Baker, F. B. (1992). Item response theory: Parameter estimation techniques. NY: Marcel Dekker.
Hambleton, R. K., & Swaminathan, H. (1985). Item response theory : Principles and applications, Boston:Kluwer-Nijhoff.
Ho, R. G., & Hsu, T. C. (1989). A comparison of three adaptive testing strategies using MicroCAT. Paper presented at the annual meeting of the American Educational Research Association, San Francisco, CA.
Carpenter,P. A., Just, M. A., Shell, P. (1990) What one intelligence test measures: A theoretical account of the processing in the Raven Progressive matrices test. Psychological Review, 97(3), pp. 404-431
Mehtre, B. M. , Kankanhalli, M. S. & Lee, W. F. (1998). Content-based image retrieval using composite color-shape approach, Information Processing & Management, 34(1), pp. 109-120
劉子鍵、梁仁楷和林世華(2001), 「圖形推理能力測驗之自動命題及施測系統」的設計、實作及評估, 第五屆全球華人學習科技研討會暨第十屆國際電腦輔助教學研討會(GCCCE/ICCAI2001)大會論文集, pp. 326-333
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