摘要
学生生活学习信息的采集、管理与分析工作需要耗费学校、教师、学生大量的时间精力,其中涉及的环节繁琐耗时,同时存在大量无用信息占用资源,而一些有效信息未得到充分利用的情况。为促进高校教育信息化发展,本文设计的基于TensorFlow框架的可视化大学生行为分析系统能够在一定程度上满足此需求,解决相关问题。其目的在于利用机器学习算法研究教育数据挖掘,进行学生数据分析,进而为学生自我提升、教师改良教育方法提供指导性依据。通过对本校学生问卷调查数据进行机器学习训练,并利用随机森林算法预测,其预测准确度可达90%以上,具有实践价值。
At present,the information work of the business process of the university management system is relatively perfect,but the collection,management and analysis of students’life and learning information need to take a lot of time and energy of schools,teachers and students,and the involved links are tedious and time-consuming.At the same time,there is a lot of useless information occupying resources and some effective information has not been fully utilized.In order to promote the development of educational informatization in colleges and universities,the visualized behavior analysis system of college students based on tensorflowframework can meet this demand and solve related problems to a certain extent.Its purpose is to use machine learning algorithm to study and analyze students’data,and to provide guidance for students’self-improvement and teachers’improvement of education methods.Through the machine learning training of the questionnaire data of the students in our school and use of the Random Forest algorithm,the prediction accuracy can reach more than 90%,which has practical value.
作者
周锐
鲍沛泽
孔钦
万凯
ZHOU Rui;BAO Peize;KONG Qin;WAN Kai(School of Information Science and Engineering,Nanjing University Jinling Conlleng,Nanjing 210089,China)
出处
《智能计算机与应用》
2020年第7期227-233,共7页
Intelligent Computer and Applications
基金
2019大学生创新训练计划项目校级(136462019007X)
