基于深度学习的智能教学系统的设计与研究

计算机科学 ›› 2019, Vol. 46 ›› Issue (6A): 550-554.

基于深度学习的智能教学系统的设计与研究

陈晋音, 王桢, 陈劲聿, 陈治清, 郑海斌

浙江工业大学信息工程学院杭州310000

出版日期:2019-06-14 发布日期:2019-07-02
通讯作者: 陈晋音(1982-),女,博士,副教授,主要研究方向为数据挖掘、智能计算等,E-mail:[email protected]
作者简介:王桢(1997-),男,硕士生,主要研究方向为数据挖掘及其应用;陈劲聿(1999-),男,硕士生,主要研究方向为数据挖掘等;陈治清(1998-),男,硕士生,主要研究方向为机器学习与应用;郑海斌(1995-),男,硕士生,主要研究方向为大数据分析、机器学习等。
基金资助:
本文受国家自然科学基金(61502423,61572439),浙江省科技计划项目(LGF18F030009),浙江工业大学重中之重学科开放基金资助。

Design and Research on Intelligent Teaching System Based on Deep Learning

CHEN Jin-yin, WANG Zhen, CHEN Jin-yu, CHEN Zhi-qing, ZHEN Hai-bin

College of Information Engineering,Zhejiang University of Technology,Hangzhou 310000,China

Online:2019-06-14 Published:2019-07-02

摘要/Abstract

摘要： 深度学习的快速发展,使其在教育领域的应用逐渐受到重视。文中介绍了一种基于深度学习的智能教学系统,该系统包括线上个性化学习推荐和线下课堂质量双向评估两部分。在线上系统中,设计基于深度学习的成绩预测和在线学习行为规律分析,并结合图像处理技术实现学习情绪分类。在线下系统中,通过训练目标检测模型、人脸检测模型和人脸分割模型,并与线上系统结合,实现了在线学习行为特征提取、线下成绩预测、学习规律分析和个性化学习推荐,同时通过线下课堂信息数据实现对高校教学质量和学生学习行为的评价和反馈。由实验结果可知,该系统不仅获取信息的渠道方便快捷,而且能够减少大量的时间成本,迎合当下线上线下相结合的新型学习教学方式,能有效提高教师的教学效率以及学生的学习效率。

Abstract: With the rapid development of deep learning,its application in education has gradually received attention.This paper introduced an intelligent teaching system based on deep learning that includes online personal learning behavior recommendation and offline bidirectional evaluation of the class quality.In the online system,based on deep lear-ning,grades prediction and online learning behavior analysis are achieved,and the image processing technology is combined to achieve learning emotion classification.In the offline system,the target detection model,face detection model and face segmentation model are trained,and the online system is combined to achieve online learning behavior feature extraction,offline grades prediction,learning regularity analysis and personal learning recommendation.The experimental results show that this system not only facilitates the access to information,but also reduces the time cost,which effectively improves the teaching efficiency of teachers and the learning efficiency of students.

Key words: Bidirectional eva-luation, Deep learning, Face recognition, Intelligent course, Personalized learning recommendation

中图分类号:

TP319

陈晋音, 王桢, 陈劲聿, 陈治清, 郑海斌. 基于深度学习的智能教学系统的设计与研究[J]. 计算机科学, 2019, 46(6A): 550-554. https://doi.org/

CHEN Jin-yin, WANG Zhen, CHEN Jin-yu, CHEN Zhi-qing, ZHEN Hai-bin. Design and Research on Intelligent Teaching System Based on Deep Learning[J]. Computer Science, 2019, 46(6A): 550-554. https://doi.org/

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