摘要
计算机语言类课程是计算机专业本科阶段重要的系列课程之一,如何划分理论与实践课课时比例仍缺乏科学合理的方法指导.提出基于BP神经网络的教学行为指导方法,根据学生及课程的具体情况自适应调整理论实践课课时比例.用层次分析法构建合理的语言课程教学评价指标体系,并通过神经网络模型输出自主学习因子指导教学.实践证明,该方法在实际教学应用中取得了良好的教学效果,为语言类课程教学行为提供了有效的方法指导.
Computer language courses are important for computer undergraduates. In order to solve the problem of theory and practice periods arranging, presents a novel method for teaching behavior guidance based on back-propagation artificial neural network （ ANN-BP ）. According to practical situation, the period proportion of theory and practice is adaptive adjusted by using this algorithm. A teaching evaluation system for computer language courses is established by using analytic hierarchy process. The neural network model based on BP algorithm generates an autonomous learning factor which to guide the teaching behavior. Teaching practice shows that the proposed method obtains a better result in the actual teaching process, which provides an effective method instruction of computer language teaching.
出处
《高师理科学刊》
2017年第5期77-81,共5页
Journal of Science of Teachers＇College and University
基金
忻州师范学院教学改革研究项目(JGYB201527)
关键词
人工神经网络
计算机语言类课程
层次分析法
教学指导
artificial neural network
computer language courses
analytic hierarchy process
teaching guidance
