Treffer: Applying Ordering Theory to Improve the Performances of Bayesian Network based Computerized Diagnostic Test effects － Using The “Number of Sequence and Geometrically Sequence“ in Elementary School Math in Grade 5 as an example

The research of this project is applies ordering theory to improve the performance of Bayesian network based computerized diagnostic test effects. Build computerized automatic on-line adaptive diagnostic test system and teaching-aid system to test and verify student performance. Predict the wild Bayesian network based function and study selected concepts from a student's examination. Predict with fewer questions, the diagnosis of problems that appear after learning. Teachers and students can be able to understand whether the learner is already totally familiar with relevant skills. Remedying the problems that students still have or dealing with the questions that the student isn’t able to answer. The result of this study will tell teachers and students in grade five who learned the unit, it can quickly diagnose each student’s individual learning situation and reduce the diagnosis of the question quantity and testing time. The dynamic teaching animation by Swish max software to cooperate with multimedia study, to improve students’ interest in studying. Also reduce the obstacle of study time. After the students finish this study, whenever a computer connects with internet, students can be suitable for individual diagnosis and assist teaching easily, it also helps more pupils with this issue. The detection from a result of this study： a. Whether the students can be pass diagnosis or not, the student’s item relational structure can still get results from the Bayesian Network.（The average dynamic threshold value is 0.9357） b. As a result of doing the system’s remedy teaching, the student gets a higher percentage raising t through the rate. The average incidence of wrong answers can be reduced effectively.The test of the average score is higher than the first time. c. There’s comparison between the adaptive test and the all the test questions in the Bayesian network’s inference. Both test results are similar. The average tests differ by 1.4%. Therefore, building of a computerized system with adaptive test of student’s ...