摘要
对高校教师授课效果客观评教,依赖于评价内容的科学设计。以教学指征反映教学过程构成评教内容的多维设计结构。设计教学评价维度的数量和内容要依靠多种方法综合确定。本文通过评述和总结国内外大学的评教设计方法,得出能体现多维结构和综合体系的建模方法,即在独立定性分析基础上再使用验证性的因素分析法。教学的多维度特征应是考量不同学科、学校文化和专业背景在长期实践教学中的特点自然形成,不能相互模仿。Feldman的19维度评教量表结合SEEQ的9维度评教结构,构成目前多维评教结构的基本框架。我国高校还应根据中国文化和国情,添加"育人"和"楷模"等高于"教学"的指征,形成有中国特色的"教育"行为范畴的维度指征。
The scientific design of the teaching evaluation contents play a key role for the objective rating on teaching effectiveness. Design of evaluation contents should be multi-dimensional structure system. The quantities and contents of the evaluation dimensions should be determined by means of different methods integrally. It’s proposed in this paper,for the modeling method characteristic of multidimensional structure and integral system,namely the confirmatory factor analytic method based on independent qualitative analyses,by way of the estimation of the design results of the teaching evaluation in universities in China and other countries,especially the summarization of the multidimensional evaluation designs which are applied widely recently. The multidimensional character of teaching behavior form naturally through the estimation of different academic subjects,different campus culture and different majors' background during long-term teaching practice,and should not be imitated. 19-dimension evaluation scale proposed by Feldman and 9-dimension evaluation structure constituted in SEEQ consist of the basic frame of the current evaluation structure. In addition,Chinese universities,in line with the China's situation and culture,supplement indexes such as "educating" and "model" which beyond "teaching" to define the Chinese style dimensions belong to "education" region.
作者
赵武
黄丹
ZHAO Wu;HUANG Dan(Henan Polytechnic University School of Mechanical and Power Engineering;Henan Polytechnic University School of Materials Science and Engineering, Jiaozuo,Henan 454000,China)
出处
《教育教学论坛》
2016年第43期208-209,共2页
Education And Teaching Forum
基金
<机械制造技术基础>河南省精品资源共享课程课题资助
关键词
教学评价
SEEQ
多维度结构
因素分析法
Teaching Evaluation
SEEQ
Multidimensional Structure
Factor Analysis Method