计算机科学
可靠性
层次分析法
过程(计算)
人工智能
熵(时间箭头)
领域(数学分析)
机器学习
工业工程
运筹学
量子力学
操作系统
物理
工程类
数学分析
数学
法学
政治学
作者
Ruhan Wang,Jiahao Lyu,Qingyun Xiong,Junqi Guo
标识
DOI:10.1007/978-3-030-78270-2_67
摘要
Artificial intelligent technology can realize multi-angle analysis and feedback of teaching process. This paper provides an innovative auxiliary for classroom teaching evaluation and fills in the lack of teacher behavior analysis in AI application. Firstly, a 3D-MobileNet framework is proposed for behavior recognition, which can process time-domain information for the video through layered training. Next, we design a comprehensive model by using both the analytic hierarchy process and entropy weight method (AHP-EW) to output the quantitative results of the teaching evaluation in three dimensions. This model combines the subjective and objective weights through a statistical optimization strategy to improve the credibility. Finally, we test our model on a 45-min teaching video, and compare it with the existing model in various aspects, proving that our method is highly feasible and competitive.
科研通智能强力驱动
Strongly Powered by AbleSci AI