Evaluation Method of Classroom Teaching Effect Under Intelligent Teaching Mode

被引:15
作者
Chen, Jing [1 ]
Lu, Hui [2 ]
机构
[1] SIAS Coll Zhengzhou, Acad Affairs & Sci Res Off, Xinzheng 451100, Peoples R China
[2] Inner Mongolia Univ, Coll Comp Sci, Hohhot 010012, Peoples R China
关键词
Intelligent course; Teaching mode; Classroom teaching effect; Cuckoo algorithm; Extreme learning machine;
D O I
10.1007/s11036-022-01946-2
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In order to improve the accuracy and performance of classroom teaching effect evaluation, an intelligent teaching mode classroom teaching effect evaluation method is proposed. Based on the characteristics of intelligent teaching mode, an intelligent teaching effect evaluation index system including five indexes of basic quality, teaching attitude, teaching method, teaching ability and teaching effect is constructed. After obtaining the scores of each index by expert scoring, it is input into the cuckoo search algorithm extreme learning machine evaluation model and solved by objective function, obtain the final score of teaching effect evaluation. The experimental results show that the proposed method can effectively improve the evaluation accuracy of classroom teaching effect of intelligent teaching mode, and provide a new method for classroom teaching effect evaluation.
引用
收藏
页码:1262 / 1270
页数:9
相关论文
共 20 条
[1]  
An F. J., 2018, Comput. Simul., V35, P439
[2]   Evaluation of information and communication technology sector in the teaching process and strategic collaboration between universities and industry [J].
Cvetkovic, Biljana Novkovic ;
Gligorijevic, Milan ;
Petkovic, Dalibor ;
Jovic, Srdan ;
Milovancevic, Milos ;
Nikolic, Vlastimir .
COMPUTER APPLICATIONS IN ENGINEERING EDUCATION, 2019, 27 (03) :653-662
[3]   An Introduction to Key Technology in Artificial Intelligence and big Data Driven e-Learning and e-Education [J].
Gao, Peng ;
Li, Jingyi ;
Liu, Shuai .
MOBILE NETWORKS & APPLICATIONS, 2021, 26 (05) :2123-2126
[4]   An AI-Application-Oriented In-Class Teaching Evaluation Model by Using Statistical Modeling and Ensemble Learning [J].
Guo, Junqi ;
Bai, Ludi ;
Yu, Zehui ;
Zhao, Ziyun ;
Wan, Boxin .
SENSORS, 2021, 21 (01) :1-28
[5]   Crowdsourced Peer Learning Activity for Internet of Things Education: A Case Study [J].
Hussein, Ahmed ;
Barhamgi, Mahmoud ;
Vecchio, Massimo ;
Perera, Charith .
IEEE Internet of Things Magazine, 2019, 2 (03) :26-31
[6]  
Kanan AM., 2019, AM J APPL MATH, V7, P152, DOI [10.11648/j.ajam.20190706.11, DOI 10.11648/J.AJAM.20190706.11]
[7]   Automatic Generation and Optimization of Test case using Hybrid Cuckoo Search and Bee Colony Algorithm [J].
Lakshminarayana, P. ;
SureshKumar, Dr T. V. .
JOURNAL OF INTELLIGENT SYSTEMS, 2021, 30 (01) :59-72
[8]   Extreme learning machine with local connections [J].
Li, Feng ;
Yang, Jie ;
Yao, Mingchen ;
Yang, Sibo ;
Wu, Wei .
NEUROCOMPUTING, 2019, 368 :146-152
[9]  
Li Y., 2019, MICROCOMPUT APPLICAT, V35, P128
[10]   Contour Stella Image and Deep Learning for Signal Recognition in the Physical Layer [J].
Lin, Yun ;
Tu, Ya ;
Dou, Zheng ;
Chen, Lei ;
Mao, Shiwen .
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING, 2021, 7 (01) :34-46