Algorithm for automatically evaluating student skill levels based on ID3 decision tree classification model
With the continuous progress of educational technology,automated student skill assessment has become an important research direction in the field of education.This study develops an algorithm based on the ID3 decision tree classification model for automatically evaluating the skill level of students.Considering the subjectivity and efficiency issues of traditional evaluation methods,an objective and efficient automated evaluation method is proposed,which can process a large amount of student learning data and provide personalized evaluation results.We preprocessed the collected student learning data,identified key features,constructed an ID3 decision tree model,and validated it on an independent test set.The experimental results show that the model achieved an accuracy of 80.32%on the test set,demonstrating good predictive performance.The automatic evaluation algorithm based on ID3 decision tree proposed in this study provides a new tool for the education field,which helps to improve the efficiency and objectivity of student skill assessment.
万方数据
维普
