An ICT Teaching Model with Computerized Adaptive Test - Using The“ Factor and Multiple“unit in Elementary School of grade 5 Math as an example

碩士 === 亞洲大學 === 資訊工程學系碩士班 === 96 === Based on expert knowledge structure and Bayesian Networks, this research aims to establish a Computerized Adaptive Diagnostic Test to assess the 5th grade students’ knowledge and performance in mathematic topic ‘Factor and Multiple’ at primary school and to dev...

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Bibliographic Details
Main Authors: CHEN CHIEN CHENG, 陳建政
Other Authors: guo ba chen
Format: Others
Language:zh-TW
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/51392454568169298264
Description
Summary:碩士 === 亞洲大學 === 資訊工程學系碩士班 === 96 === Based on expert knowledge structure and Bayesian Networks, this research aims to establish a Computerized Adaptive Diagnostic Test to assess the 5th grade students’ knowledge and performance in mathematic topic ‘Factor and Multiple’ at primary school and to develop a set of digital remedial teaching materials to instruct teachers. It is expected that this pedagogy can meet different needs of students and provide different levels of tests for students of different abilities. This research firstly analyses the content of ‘Factor and Multiple’ and establishes expert knowledge, upon which an adequate set of test questions is designed for pre-testing students. Subsequently, students’ knowledge structure on this mathematic topic is analysed and classified in terms of the pre-test results. Furthermore, a computerized adaptive diagnostic test bank and rules of selecting questions for test is constructed based on students’ knowledge structure. Additionally, a remedial instruction is completed by referring to student knowledge structure and expert knowledge structure and leads to the development of digital remedial teaching material. This teaching material was used at school with an experiment where one group of students used digital remedial teaching material and the other did not. The results of this experiment in relation to teaching outcomes between the two groups are summarized as follows. 1. The accuracy and speed of diagnosing students’ mistakes, sub-skills and unit objective achievement by applying Bayesian Networks combing with expert knowledge structure is similar to that of manual check by specialists. 2. It is estimated that the number of questions can be reduced by 20% by using Computerized Adaptive Diagnostic Test for ‘Factor and Multiple’. The accuracy rate of predication is 97.13%, which implies that the predication capability of using Computerized Adaptive Diagnostic Test matches that of having a complete test. 3. The students of the group using digital remedial teaching material show significant improvements in their begin test results comparing with the results of the group students without using digital remedial teaching materials. 4. The students of the group using digital remedial teaching material show significant improvements in their final test results comparing with the results of the group students without using digital remedial teaching materials. 5. Students whose performance are at or below average mark (80-89 or below 80) have made significant progress in final test results after using digital remedial teaching materials. This shows that digital remedial teaching materials produce a marked effect for students in this group.