联合PDCA与SVM的教学模式设计与质量评价研究

Research on teaching mode design and quality evaluation combined with PDCA and SVM

科学化的教学模式是持续提升教学质量的关键,论文构建教学任务实施PDCA环,并采用PSO算法对SVM模型的惩罚系数和核函数参数进行优化,获得了用于教学质量评价的PSO-SVM模型。将教学任务实施PDCA环应用于高等数学教学中,分别采用SVM模型和PSO-SVM模型对教学质量进行评价。评价结果表明,PSO-SVM模型对教学质量评价的准确率明显高于SVM模型,且两个模型的运行时间相差甚微,同时PDCA教学模式明显优于传统教学模式,特别是对学习难度比较大知识教学效果更为突出,这对其它课程的教学实施具有一定的参考价值。

Scientific teaching mode is the key to continuously improve teaching quality.This paper constructs a PDCA ring for teaching tasks,optimizes the penalty coefficient and kernel function parameters of SVM model by PSO algorithm,and obtains PSO-SVM model for teaching quality evaluation.The teaching task implementation PDCA ring is applied to higher mathematics teaching,and SVM model and PSO-SVM model are used to evaluate the teaching quality.The evaluation results show that the accuracy of PSO-SVM model in the evaluation of teaching quality is significantly higher than that of SVM model,and the running time of the two models has little difference.At the same time,PDCA teaching mode is significantly better than the traditional teaching mode,especially for the teaching effect of knowledge with great learning difficulty,which has a certain reference value for the teaching implementation of other courses.