基于AGA—BP算法的课堂教学质量评估研究  

The Quality Evaluation for Class Teaching Based on AGA—BP Algorithms

作　　者：袁力哲[1] 陈燕生[1] 牟鹏昆[1] 

机构地区：[1]炮兵指挥学院三系,河北廊坊065000

出　　处：《微计算机信息》2011年第1期240-241,179,共3页Control & Automation

基　　金：学院青年创新基金资助(基金编号不公开)

摘　　要：课堂教学质量评估是教学管理工作的重要环节。本文从教学态度等8个方面建立了课堂教学质量评估指标体系,确定了评估系统的计算方法,提出了一种将遗传算法与BP神经网络结合而成的AGA-BP混合算法用于高校教师课堂教学质量评估中。实践表明,AGA-BP混合算法与改进的BP算法,前者的收敛速度和学习精度要比后者的要更快更高,能为课堂教学质量评估研究提供有意义的参考价值。The quality evaluation for class teaching is a most important part of teaching management process.It presents the assessment index system of class quality evaluation including teaching attitude and so on.A calculation method of the evaluation system is established.The hybrid algorithm with adaptive genetic algorithms and BP neural network named AGA-BP algorithm is used to assess the quality of class teaching in higher education.The computation results shows that the convergence speed and learning accuracy of AGA-BP algorithm is superior than that of the improved BP neural algorithm,which indicate that the former can provide a meaningful reference value for the study of class teaching quality assessment.

关 键 词：课堂教学质量 评估 BP网络 自适应遗传算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]