基于ID3决策树分类模型的自动评估学生技能水平的算法

Algorithm for automatically evaluating student skill levels based on ID3 decision tree classification model

随着教育技术的不断进步,自动化学生技能评估成为教育领域的一个重要研究方向。考虑到传统评估方法的主观性和效率问题,文章开发了一种基于ID3决策树分类模型的算法,用于自动评估学生的技能水平。该方法客观、高效,能够处理大量的学生学习数据,并提供个性化的评估结果。文章对收集到的学生学习数据进行预处理,确定关键特征,构建了一个ID3决策树模型,并在独立的测试集上进行了验证。实验结果表明,该模型在测试集上达到了80.32%的准确率,显示出良好的预测性能。文章提出的基于ID3决策树的自动评估算法为教育领域提供了一种新的工具,有助于提高学生技能评估的效率和客观性。

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.