学时缩减背景下基于大数据的本科教育课时优化  

Undergraduate Education Class Optimization under the Background Reduction of Class Hours on Base of Big Data

作　　者：祝夫文 段园培 朱协彬 

机构地区：[1]安徽工程大学机械与汽车工程学院,安徽芜湖241000

出　　处：《教育教学论坛》2018年第12期89-90,共2页Education And Teaching Forum

基　　金：安徽省省级振兴计划重大教学改革研究项目"工程教育专业认证下的"卓越计划"人才培养模式改革--以材料成型及控制工程专业为例"(项目编号:2015zdjy085);安徽工程大学校级本科教学质量提升计划教研项目"材料成型及控制工程专业毕业设计环节创新能力培养的改革探索与实践"(项目编号:2015jyxm22)

摘　　要：针对当前高校本科教育总学时缩减的实际现象及人工进行课时优化的不足之处,本文探讨了一种计算机辅助课时优化的模型。模型以课程知识点提取为基础,考虑了知识点的本质难度,最后通过结合实际授课学时及考试平均分,建立了反映教学效率的课时效率函数。该函数可以直接反映各个知识点的授课效率,为教师的持续改进提供数据支持。相对于人工优化,计算机辅助课时优化有可复制的优点,有利于青年教师的培养和老教师经验的数据化保存,有利于课程的可持续发展。本文的优化思想,对相关教研系统的开发有一定的参考价值。Aiming at the deficiency of the total period reduction of undergraduate education and the artificial optimization of class hours,this paper discusses a model of computer aided class optimization. The model takes the course knowledge point extraction as the base,considers the essential difficulty of knowledge points,and finally establishes the efficiency function by combining the actual teaching hours and the examination average. This function can directly reflect the teaching efficiency of each knowledge point,and provide data support for the continuous improvement for teachers. Compared with the manual optimization,the computer aided class optimization has the advantages that can be copied,which is conducive to the cultivation of young teachers and the datamation saved of the old teacher experience, which is conducive to the sustainable development of the curriculum. The optimization thought of this paper has a certain reference value to the development of the relevant teaching and research system.

关 键 词：本质难度 课时优化 效率 授课学时 

分 类 号：G642.0[文化科学—高等教育学]