- 學位論文
以知識結構及貝氏網路為基礎開發國小語文領域「說明文」教材與評量
A Study of Developing Teaching Material and Assessment for “Exposition” Teaching of Language Domain in Elementary School - Using Knowledge Structure and Bayesian Networks as tools
摘要
本研究主要目的在驗證一套國小語文領域「說明文」的數位個別指導教材之教學效果，並以知識結構為基礎，分析教材內容，再結合貝氏理論與能力指標的概念，編製試題，建立題庫以適用於電腦化診斷測驗評量系統，作為實施測驗的工具來診斷學生錯誤類型；並依據其錯誤概念即時進行適性補救教學。 本研究共分為兩階段，預試時我們以臺灣省中部四縣市國小之10個班級273名五年級學童為施測樣本。正式施測時選取臺中市國小五年級學生共計100名為研究對象。 所得資料以統計套裝軟體進行分析結果如下： 壹、預試試題信度α值為0.7795。整份試題整體鑑別度介於0.142到0.522之間。除了第1、2、6和8題之通過率達88％以上外，其餘試題通過率介於46％至86％之間之常態分配。此適性測驗預測精準度達95％，平均作答題數約11到12題，省題率達20％以上。 貳、使用此套數位個別指導教材指導學生後，其成績有明顯的進步，尤其以個別指導教學模式組的成效最為顯著，表示此數位個別指導教材有其使用價值。 叁、此套以知識結構編製的數位個別指導教材適合不同指導模式，使用此套教材進行一師對一生、一師對二生及一師對團班指導，學生的成績都有明顯進步。 肆、在補救教學的成效上，一對一、一對二與適性團班指導亦有良好效果，且以低分組學生進步最多，三種教學模式的進步分數都在10分以上。
並列摘要
The main purpose of this research is to develop a digital individual teaching material for “Exposition” teaching of Language Domain in elementary schools. We analyze the knowledge structure of teaching material content, and set the examination paper based on Bayesian Networks and the Competence Indicators. We then input into the computerized diagnosing test system, and proceed with tests for finding out students’ mistake types. It offers adaptive remedy instructions by the mistake types after taking the test online. There are two major stages to complete this study. In the first round data collection, there were 273 fifth-grade students ( from 10 elementary schools in four counties of Central Taiwan ) participated in the study. We took 100 students in Taichung City to be our research subjects in the second round. Some findings are briefly outlined as follows: 1. The Cronbach α value of formal questionnaire is 0.7795. Most of the questions have an excellent discrimination. 80％ of the questions are ranged in a medium or low difficulty level. The number of items administrated by BNAT is 11 or 12 items are omitted and prediction accuracy can reach 97％. 2. After taking the instruction, students have significant progress on their average grades. The teaching model of one v.s. one and one v.s. two are better than one v.s. a class. It shows that this digital individual remedial teaching material is useful. 3. This digital individual teaching materials made by knowledge structure is adaptable to three kinds of teaching models. 4. The Effects of Remedial Instruction for the three kinds of teaching models are very good, especially for the low proficiency learners group. The grade-point average of three kinds of teaching models improved by over 10 points.