本研究嘗試以國小自然與生活科技領域四年級之「月亮」單元為例,利用貝氏網路作為推論工具,並加入OT順序理論來決定試題的順序結構,發展一套適用於本單元的電腦適性化診斷測驗和電腦適性化補救教學系統,並探討貝氏網路應用於診斷受試者錯誤類型、子技能和單元目標的效能,並驗證此系統的成效。 研究結果發現: 1. 將紙筆診斷測驗轉換成為電腦適性化診斷測驗之後,適性化診斷測驗的施測介面穩定度高達96%,而適性測驗平均施測35題,與傳統紙筆測驗相比,平均可以節省10題,縮短了施測的時間。 2. 經過電腦適性化補救教學後,學生的平均分數進步了20分,而且達到了顯著性差異。 因此,本研究所所建置的電腦適性化學習系統,的確可以達到因材施教的目的,並且有良好的診斷效果。
The study was to develop a system based on the probability reasoning of Bayesian Network and OT theory into the Moon unit. This system was composed of On-line Adaptive Diagnostic Test System and Computerized Adaptive Remedial Instruction. The Moon unit was Nature and Life Technology course in Grade four at primary school. After taking the test, the unpracticed competence indicators of students were diagnosed individually, and then correspondent remedial instruction Flash animators were presented to them to learn. This system tried to induce the error types that students made and to validate the effect of the system. The results were as follows. 1. The stability of execution interface increased up to 96% at Computerised Adaptive Diagnostic Test System. The number of items tested by students in the Computerized Adaptive Diagnostic Test System is 35 averagely. This system can save 10 items averagely, and the test-taking time is also saved simultaneously. 2. After the Adaptive Remedial Instruction, Student’s grades increased twenty. The progress of students is significant. Therefore, the Online Adaptive Learning System proposed in this study can factually test and remedy students’ abilities individually.