Chinese Journal of Science Education 2002,, 423-439 2002, 10(4), 423-439 1 2 1 1 1 2 90 8 10 91 4 9 91 8 22 ) NII 1995 7 14, 1999 1997 (Cooperative Remotely Accessible Learning CORAL)
424 (Collaborative Visualization CoVis) Tyler1950 1996 1996, 1992a, 1992b Fan, Mak 1997 Shue1996 Knowledge Based Computer Assisted Instruction System 2001 1994 NII 1998 UCLA Homepage Education Network (http://www.then.com) ITED (Intelligent Tutoring, Evaluation and Diagnosis) CORAL 88 93 3 Dennis & Gruner, 1992 GRE 1999
425 2.1ITED 2.1 ITED 2001 2.2 Data Mining
426 2.2 () 1 0 2.1 Q i Q i (P i1, P i2,, P im ) Q input Q 1994 Evaluation Balance j Table m input j input r jr e ij e ij error_distance(q,q) = P -P m 5 m error_distance 4 3 2 r= 1
427 2.1 1 (K 1 ) 2 (K 2 ) m Q 1 P 11 P 12 P 1m Q 2 P 21 P 22 P 2m Q I P i1 P i2 P im 2.3 () 100% ()
428 Q1. Q2. 3 13 2.3 100% = 23.08% 2001 3 If ( µ ± K j > 1.5 S ) Then { Println( K j ); }, 1999; µ K j, 1999;, 1996;, 1995; 2, 1996; S = ( x x) N 1, 1988 1999 Conceptual Q1. Relation Table Q2.
429 3.1 : : : : : : 0 5 : 0 0 : 5 0 : : 3.2 : : : : : : : : 2 5 0 0 2 : 2 2 0 0 5 : 5 2 0 0 2 : 0 0 0 4 0 : 0 0 0 4 0 : 2 5 2 0 0 : : 23.08% 96% 3.1 3.2 50% Q 1 Q 2 15 5 4 3 2 1 0 2001 100%80%60%40%20%0% Q 1 Q 2 3.2 100% 80% 100% Q 1 Q 2 (1 22 11 0.8)(1 23 1) 100% 96% 3.2 Q3.
430 Conceptual Relation Table Conceptual Relation Table 3.1 Q4. 3.1 Similarity(Q i, Q j ) = ( r (M r (Q i, Q j ) W r )) Max (N(Q i ), N(Q j )) 100% N(Q i )N(Q j ) Q i Q j M r (Q i, Q j ) W r r Q i Q j W r W r C 1 W r C 2 W r C 3 C 1 C 2 C 3 C 1 C 2 C 3 C 1 2C 2 1C 3 0 Q5. (1) (2) Q6.
431 Match Yes No N No Yes N+1 3.2 (1) (2) (3) Q7 Q7. (1) (2) Q8.
432 4.1 3.2 4.1 Virtual Basic CGI Access Windows NT 24 27 362 2001 24 27 Conceptual Relation Table Conceptual Relation Table WWW JAVA WWW JAVA WWW JAVA WWW JAVA
433 4.2 - - 24 4.3 - - 25 4.4 - - 26 4.5 - - 27 4.6 - - 24
434 4.7 - - 25 4.8 - - 26 4.9 - - 27 4.24.9 3. 4.2 4.9 1. 24 27 4.104.17 2. 242627 4.
435 4.10 - - 24 4.11 - - 25 4.12 - - 26 4.13 - - 27 4.14 - - 24
436 4.15 - - 25 4.16 - - 26 4.17 - - 27 10 5. 6. 10
437 1. 1999 2. 1996, 42, 29- ()35 3. 1996 4. 1997, 6, 4, 12-15 () 5. 1999 6. 1995 () 7. 1996 8. 1997, 12, 1999;, 1999;, 1996;, 1995 D-129-D-134 9. 2001, 8, 1, 57-85 10. 1988, 6, 42, 21-30 11. 1996 NSC-90-2520-S-260-002, 52
438 12. 1998, 3 (2nd ed.). Englewood Cliffs, NJ: Prentice-Hall. 17. Dennis, V. E., & Gruner D. (1992). Computer managed instruction at Arthur Anderson &, 476-483 Company: A status report. Educational Technology, Vol. 32, No. 8, 7-16. 13. 1992a 18. Fan, Joshua Poh-Onn, Mak, Tina Kwai-Lan, &, 297, 34-38 Shue, Li-Yen (1996). Development of a 14. 1992b knowledge based computer assisted instruction, 298, 54-58 system. Paper presented at the 1996 International 15. 1994 Conference Software Engineering: education and Practice, Dnnedin, New Zealand. 16. Alessi, S. M., & Trollip S. R. (1991). Computerbased instruction: Methods and development 19. Tyler, R. W. (1950). Basic principles of curriculum and instruction. Chicago: University of Chicago Press.
439 Analysis and Improvement of Test Items for a Network-based Intelligent Testing System** Gwo-Jen Hwang 1 *, Judy C. R. Tseng 2, Carol Chu 1, and Jing-Wu Shiau 1 1 Information Management Department, National Chi Nan University, Pu-Li, Nan-Tou, Taiwan 545, R.O.C. 2 Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu, Taiwan, 300, R.O.C. Abstract During the learning process, it is important to evaluate the learning status of the students, especially in a network-based learning environment that provides personalized subject materials. To have an integrated and shared test bank, it is necessary to have several educational experts cooperate through computer networks. In some previous work, researchers have proposed techniques to cope with redundancy, consistency and integrity problems when educators provide test items through computer networks. However, the correctness and accuracy of the redundancy and consistency checking are not desirable, which will significantly affect the quality of the item bank. In this paper, we propose a semantic analysis-based method to cope with these problems. Some experiments on "Biology" course of senior high schools have shown that our approach can achieve more accurate results. Key words : Network-based Testing, Item Bank, Redundancy Analysis, Consistency Analysis, Distance Learning. * To whom all correspondences should be sent. ** This study is supported by the National Science Council of the Republic of China under contract number NSC- 90-2520-S-260-002.