赵敏 詹玮



摘 要: 基于深度学习算法设计教学质量评价系统,系统自动生成教师教学质量评价报告,分析教学过程中存在的问题,给出优化建议。教学质量评价系统包括用户管理、网上评价、数据管理、评价结果查询、教学质量分析5个单元,用户进入系统后为教学质量打分。基于教学质量评价指标体系内容,卷积神经网络学习专家教学质量评价样本,构建卷积神经网络教学质量评价模型。将教学质量评价测试样本输入模型,模型输出结果即为教学质量评价分析结果,主要分析教学存在的问题,提出改进建议。系统可统计不同学科教学质量评价情况,统计不同学科教学质量占比情况,智能化程度较高,值得推广使用。
关键词: 深度学习; 用户; 教学质量; 数据管理; 评价系统; 智能化程度
中图分类号: TN911.1?34; TP319 文献标识码: A 文章編号: 1004?373X(2020)13?0143?04
Teaching quality evaluation system based on deep learning algorithm
ZHAO Min1, ZHAN Wei2
(1. School of Data Science and Information Engineering, Guizhou Minzu University, Guiyang 550025, China;
2. College of Clinical Medicine, Guizhou Medical University, Guiyang 550025, China)
Abstract: The teaching quality evaluation system is designed based on the deep learning algorithm. The system can automatically generate teachers′ teaching quality evaluation report, analyze the problems existing in the teaching process and give optimization suggestions. The teaching quality evaluation system includes 5 units, named user management, online evaluation, data management, evaluation result query and teaching quality analysis. The user scores the teaching quality after entering the system. On the basis of the content of teaching quality evaluation index system and the teaching quality evaluation samples of convolutional neural network learning experts, a convolutional neural network teaching quality evaluation model is constructed. Input the teaching quality evaluation test sample into the model, the output result of the model is the teaching quality evaluation and analysis results, which mainly analyzes the problems existing in the teaching. In addition, the suggestions for improvement is put forward. The system can count the evaluation of teaching quality of different subjects and the teaching quality proportion of different subjects. It is highly intelligent and worth popularizing.
Keywords: deep learning; user; teaching quality; data management; evaluation system; intelligence level
0 引 言
深度学习是机器学习研究领域的延伸,是实现人工智能的有效方式,近几年,关于深度学习的研究成为人工智能领域的研究重点[1?2]。深度学习理论在图像识别、语音识别、语言处理、数据挖掘等方面取得了优异成绩。深度学习算法实现方式较多,如卷积神经网络、多层神经元的自编码神经网络、深度置信网络等[3]。
教学质量评价系统是对教师阶段性教学效果的评估,为掌握教师教学能力、提升教学质量提供有利分析依据[4]。评价教学质量过程中,涵盖评价指标较广,形成大规模复杂数据,大部分教学质量评价系统仅能显示教师教学质量,不具备智能分析教师存在的问题,制定合理建议的功能,或者这些功能需要人工完成[5?6]。……