{"title":"Research on the Evaluation Methods of English Teaching Quality in the Context of Online Education","authors":"Xueqiang Wang","doi":"10.1080/13614576.2022.2154691","DOIUrl":null,"url":null,"abstract":"ABSTRACT With the development of online education, the evaluation method of teaching quality has also received wide attention. This paper took the “Comprehensive English” course on the Massive Open Online Courses (MOOC) platform as an example, established teaching quality evaluation indicators, designed an evaluation method based on a back-propagation neural network (BPNN), optimized the parameters of the BPNN by the improved genetic algorithm (GA), and established an improved GA-BPNN model. The results found that the error between the output of the improved GA-BPNN model and the actual value was the smallest, between 0.01 and 0.04, showing that the model was stable; the mean absolute percentage error (MAPE) and root-mean-square error (RMSE) of the improved GA-BPNN model were 0.051 and 4.778, respectively, which were superior to BPNN and GA-BPNN models. The results verify the reliability of the improved GA-BPNN model. The model can be applied in practical teaching.","PeriodicalId":35726,"journal":{"name":"New Review of Information Networking","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Review of Information Networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/13614576.2022.2154691","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Social Sciences","Score":null,"Total":0}
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Abstract
ABSTRACT With the development of online education, the evaluation method of teaching quality has also received wide attention. This paper took the “Comprehensive English” course on the Massive Open Online Courses (MOOC) platform as an example, established teaching quality evaluation indicators, designed an evaluation method based on a back-propagation neural network (BPNN), optimized the parameters of the BPNN by the improved genetic algorithm (GA), and established an improved GA-BPNN model. The results found that the error between the output of the improved GA-BPNN model and the actual value was the smallest, between 0.01 and 0.04, showing that the model was stable; the mean absolute percentage error (MAPE) and root-mean-square error (RMSE) of the improved GA-BPNN model were 0.051 and 4.778, respectively, which were superior to BPNN and GA-BPNN models. The results verify the reliability of the improved GA-BPNN model. The model can be applied in practical teaching.
期刊介绍：
Information networking is an enabling technology with the potential to integrate and transform information provision, communication and learning. The New Review of Information Networking, published biannually, provides an expert source on the needs and behaviour of the network user; the role of networks in teaching, learning, research and scholarly communication; the implications of networks for library and information services; the development of campus and other information strategies; the role of information publishers on the networks; policies for funding and charging for network and information services; and standards and protocols for network applications.
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