高中職入學制度中在校成績採計校正方式之比較 作者:陳柏熹(國立臺灣師範大學教育心理與輔導學系副教授)、邱佳民(國立臺灣師範大學心理與教育測驗研究發展中心研究員)、曾芬蘭(國立臺灣師範大學心理與教育測驗研究發展中心副主任)

卷期：55卷第2期
日期：2010年6月
頁碼：115-139
DOI：10.3966/2073753X2010065502004

摘要：

高中職免試入學為教育部目前的重要政策。根據該項政策，在校成績將成為各項入學管道的主要參考資訊。但由於各校對成績的評分標準與評分方式皆不相同，因此如何使在校成績採計作到公平性將成為一項重要的問題。本研究主要目的是發展校正不同學校在校成績的模式，以使在校成績能盡量做到像國中基本學力測驗（以下簡稱國中基測）一般的公平性。研究方法是採用多元迴歸分析與階層線性模式來校正在校成績，以瞭解在校成績相關的自變項對國中基測成績之解釋變異量。其中依變項為國中基測成績，自變項為學生在校成績Z分數、依學校標準差校正後的學生成績Z分數，以及學校在全國中的Z數。研究資料為2008年參加國中基測之臺北縣學生之國中基測成績與在校3年成績。結果顯示，若只用學生在校成績Z分數而不作任何校正，對未來國中基測成績之可解釋變異量介於65%～80%，使用迴歸分析法的效果略優於階層現性模式；加入學校標準差後其可解釋變異量幾乎都沒有提升；再加入學校在全國中的Z數後其可解釋變異量提高至72%～89%，此時階層線性模式略優於多元迴歸。根據此結果，未來若能在使用學生在校成績時加入某些會考或學力檢測中各校相對表現來進行校正，將更能反映出學生能力在全國母群體中的相對位置，提高在校成績使用之公平性。

關鍵詞：多元迴歸、在校成績、高中職入學制度、階層線性模式

《詳全文》

A Comparison of Different Statistical Moderation Methods in Applying the GPA to Senior High Schools Author: Po-Hsi Chen(Department of Educational Psychology and Counseling, National Taiwan Normal University),Jia-Min Chiou(Research Center for Psychological and Educational Testing, National Taiwan Normal University),Feng-Lan Tseng(Research Center for Psychological and Educational Testing, National Taiwan Normal University)

Vol.&No.：Vol. 55, No. 2
Date：June 2010
Pages：115-139
DOI：10.3966/2073753X2010065502004

Abstract：

Based on the Guidelines Regarding the Multiple Admission Process to Comprehensive and Vocational High Schools, admission to senior high school without entrance examinations has been proposed and advanced by the Ministry of Education in Taiwan. Without the reference of the entrance exams, the grade point average (GPA) has been adopted as an alternative in admission selection. However, due to different grading criteria and standards among schools and teachers, the application of GPA in admission decision involves troublesome disputes. The goal of this research is to discuss the potential controversies involved in the use of GPA in admission selection and to compare different statistical adjustment methods to enhance the comparability of GPA among schools. Multiple regression and hierarchical linear modeling (HLM) were investigated. The dependent variable of these methods was the students’ scores in the Basic Competency Test for junior high school (BCTEST). The predictive variables were the Z score of GPA in junior high school, the Z score of GPA adjusted by the standard deviation of junior high school, and the Z score of GPA adjusted by the standard deviation of school combined with the Z scores of junior high school in the BCTEST. Data was collected from the students who attended the BCTEST in 2008. The results indicated that when the Z score of GPA was used alone, the percentage of the explained variance to the BCTEST scores ranged from 65% to 80%. When the Z score of GPA was adjusted by the standard deviation of junior high school, the percentages of the explained variance to the BCTEST scores were similar to the case where the Z score of GPA was used without adjustment. When the Z scores of junior high school in the BCTEST was taken into account, the percentages of the explained variance to the BCTEST scores ranged from 72% to 89%. The moderation effects of multiple regression and HLM were similar. It is suggested that when the GPA is used as an admission requirement to senior high school, an equating procedure can be employed to enhance its comparability.

Keywords：multiple regression, average grade point, admission to school, hierarchical linear modeling