Case Study on the Teaching of Artificial Intelligence Basic Algorithm Training Course
In order to solve the problems of disjointed and poorly coherent experimental content of multiple core algorithms in existing artificial intelligence courses,this paper designs an experimental teaching case of an English knowledge profiling system that integrates multiple basic algorithms.The case,based on several valuable data existing in the education field(such as training process data,learning performance data,etc.),takes the English subject as the breakthrough point,starting from the three perspectives of"basic knowledge level-learning engagement level-knowledge mastery level",using decision tree classification,K-means clustering and other methods to generate multi-properties labels,and comparing the performance of the algorithms.The training framework integrates multiple machine learning algorithms to generate profiling systems,forming a comprehensive training teaching case covering"system design-coding-analysis-display".Several rounds of teaching practice have shown that introducing projects throughout the experimental process can,to some extent,enhance students'innovative practical ability and comprehensive application ability.
Profiling systemArtificial IntelligenceDecision treeJunior middle school English teachingTeaching cases
万方数据
维普
