华东师范大学学报(教育科学版) ›› 2021, Vol. 39 ›› Issue (7): 84-91.doi: 10.16382/j.cnki.1000-5560.2021.07.008

• 教师队伍建设 • 上一篇    下一篇

基于学生成绩残差分解技术的教师教学质量评价

雷万鹏1, 马红梅1, 黄华明2   

  1. 1. 华中师范大学 教育学院/湖北省基础教育研究中心,武汉 430079
    2. 韶关学院 教育学部,韶关 512005
  • 出版日期:2021-07-01 发布日期:2021-07-02
  • 基金资助:
    湖北省教育科学规划重大招标课题“湖北省师范教育改革发展研究”(2018ZDZB11);韶关市教育局“韶关市基础教育学校公办教师‘县聘校管’改革政策研究”

Evaluate Teaching Performance by Residuals of Student Achievement

Wanpeng Lei1, Hongmei Ma1, Huaming Huang2   

  1. 1. Faculty of Education, Central China Normal University/Hubei Institute for Basic Education Research Wuhan, 430079
    2. Faculty of Education, Shaoguan University Shaoguan, 512005
  • Online:2021-07-01 Published:2021-07-02

摘要:

运用教育生产函数方法,在控制学生特征、教师特征和学校特征后,学生成绩的预测值与班级均值之差可视为教师教学对学生学业发展的净效应,将此残差值在班级层面加总平均即为教师教学质量的效应量。本文基于课题组在湖北和广东两省收集的数据,利用多层线性模型预测学生成绩,结合学生成绩残差分解技术讨论语文、数学和英语三科教师教学质量的效应量差异。本研究的主要发现是:第一,语文、数学和英语三个科目的教师教学质量的边际效应介于0.3?0.5个标准差间,且数学教师的教学质量对学生成绩的影响最大;第二,教师教学质量的个体间差异较大,若将教学质量处于平均水平的教师替换为最优秀的教师,全班学生的成绩可整体提升0.3个标准差;而将其替换为教学质量最差的教师后,全班成绩将集体下滑0.5-0.7个标准差。在如何科学评价教师“教得好”方面,本研究具有较大的应用价值。

关键词: 教师评价, 教学质量, 学生成绩, 残差分析

Abstract:

Error-component analysists argue that after netting out the effects of student background, teacher credentials and school characteristics, the residuals of test scores generated by subtracting predicted values from the class-level mean can be regarded as teachers’ effect on pupils’ achievement. The paper tests this idea by using self-collected teacher-student matched data from Hubei and Guangdong province. Residual analyses show that, (1) Marginal effects of teaching performance of teachers instructing Chinese Language Art, Math and English are among 0.3?0.5 standard deviations, among which the magnitude of Math teachers’ effect is the largest. (2) There are huge individual differences among teachers in terms of teaching performance. If a teacher of average quality were replaced by the most effective one, the whole class would witness a net gain of 0.3?1.0 standard deviations. On the contrary, if he or she were replaced by the worst colleague, mean performance of the class he or she taught would go down by 0.5?0.7 standard deviations. Policy implications of this article are obvious with regard to evaluating teachers’ performance.

Key words: teacher assessment, teaching performance, students’ academic achievement, residual analysis