数据驱动的知识点智能分析模型构建与运用

Construction and Application of Knowledge PointsIntelligent Analysis Model driven by data

学生对知识点的掌握程度是反映其学习状况的一个重要标志,更是学生进行个性化学习的一种重要方式,对于提高学生的学习效果和教师的教学质量有重要影响。因此,如何借助数字化学习工具来精准诊断和评估学生对知识的掌握情况成为了当前研究热点之一。以Rasch模型作为研究的依据,以数据挖掘技术作为研究手段,基于Rasch模型特点,建构了智能学习系统中学生知识点掌握水平分析模型。通过对学生的考试成绩进行挖掘,基于考试成绩精准分析每位学生的知识掌握情况,以此实现个性化学习。通过对某校2次物理月考成绩进行采集和分析,对实验结果进行处理与分析,得出相关结论,进一步验证模型的可行性。

The students mastery of knowledge points is an important indicator of their learning situation,but also an important approach of personalizing their learning,which plays a key role in improving students learning and teachers teaching quality.Therefore,how to accurately diagnose and evaluate students mastery of knowledge by intelligent means has become one of the current research hotspots.Students mastery of knowledge is an important indicator of their learning status and an important way of personalizing their learning,which plays a key role in improving students learning and teachers teaching quality.Therefore,it has become one of the hot topics of current research to accurately diagnose and assess students mastery of knowledge through intelligent means.This paper uses the Rasch model as the basis for research and data mining technology as the research tool.Based on the characteristics of the Rasch model to construct an analysis model of students knowledge mastery level in an intelligent learning system.By mining students examination results,the knowledge mastery of each student is accurately analyzed based on the test scores,thereby realizing personalized learning.By collecting and analyzing the results of two monthly physics exams in a certain school,the experimental results were processed and analyzed to draw relevant conclusions and further validate the feasibility of the model.