家庭語文環境、教室學習環境與五歲特殊幼兒語言能力的關係

Effects of Home Literacy and Classroom Environments on the Language Ability of 5-year-old Young Children with Special Needs

本研究根據Bronfenbrenner生態系統理論，以「特殊教育長期追蹤資料庫」（SNELS）進行次級資料分析，探討家庭語文環境、教室學習環境與特殊幼兒語言能力的關係。研究對象是933位具全國代表性的五歲特殊幼兒，其中約2/3為男生，障礙類別以發展遲緩兒最多，約占1/3，約六成來自社經地位較低的家庭。研究者先以相關分析、t檢定、單因子變異數分析了解幼兒特質、家長背景、家庭語文環境以及教室學習環境等變項與特殊幼兒語言能力的關聯或差異，再進一步以階層迴歸模式探究家庭語文環境以及教室學習環境對語言能力的預測力。研究結果發現：特殊幼兒語言能力與幼兒特質、家長背景、家庭語文環境和教室學習環境均達顯著相關或顯著差異。整體迴歸模式可以解釋特殊幼兒語言能力總變異的53.4％，其中，幼兒特質對語言能力的解釋量最高達47.1%。控制幼兒特質及家長背景變項後，家庭語文環境（家長常和孩子聊學校事、家中從事多元語文活動）和教室學習環境（師生關係、支持服務）皆為有效的預測變項，可以增加語言能力5.5%的變異量。

Based on ecological systems theory, this study explored how the language ability of children with special needs is related to their home literacy and classroom environments. This study involved conducting secondary data analysis from the Special Needs Education Longitudinal Study (SNELS) as a nationally representative sample in Taiwan. The research sample comprised 933 five-year-old children, approximately two-thirds of these children were boys, and the most common disability reported was developmental delay (31.5%). The results revealed that there were statistically significant differences in or associations with the language ability of children with special needs, across different child characteristics, family background, home literacy environment, and classroom learning environment. The overall hierarchical multiple regression model explained 53.4% of the total variance in the language ability of children with special needs, while child characteristics variables accounted for most of the variance explained by the model (47% ). After child and family background variables were controlled for, the identified effective predictors of the language ability of children with special needs included talking with children about their school experiences frequently, engaging in various literacy activities at home, maintaining positive teacher-student relationships, and providing supportive services at classroom. These variables could increase 5.5% of the variance explained by the model.