指向深度学习的课堂教学  

Deep Learning-Oriented Classroom Teaching

作　　者：柏灵[1] 侯影 徐向红[1] BAI Ling;HOU Ying;XU Xianghong(School of Mathematics,Jilin University,Changchun 130021,China)

机构地区：[1]吉林大学数学学院,长春130012

出　　处：《大学数学》2023年第4期98-105,共8页College Mathematics

基　　金：吉林省本科教学教改重点项目(JLJY202181448668);吉林大学本科教改项目——新农科背景下公共数学课程体系建设与实践(2021XZD076)。

摘　　要：基于内容的结构关联性,针对二维随机变量函数的分布的知识点进行课堂教学设计.层层递进的问题链引导和推动着学生的思考,最终达到高阶性深度学习的目的.课后通过对学生的调查问卷进行对比分析,显示本教学设计对教学内容的分析和拓展得到学生的高认可度,教学质量和效果明显提高.Based on the structural relevance of the learning contents,this paper carries out the classroom teaching design for the distribution of knowledge points of two-dimensional random variable function.The students’thoughts are guided and promoted by teachers in the classroom using the chain of progressive questions.Finally,they improve ability of the advanced deep learning.After class,the comparative analysis of students’questionnaires shows that the structural analysis and expansion about the contents of this design have been highly recognized by students,and the teaching quality and effect have been significantly improved.

关 键 词：深度学习 问题驱动 概率密度函数 随机变量的函数 

分 类 号：O212.1[理学—概率论与数理统计]