{"title":"基于支持向量机的高校在线实验教学质量综合评价","authors":"Jianmeng Ou, Dongdong Lin, Zhitao Zheng","doi":"10.3991/ijet.v18i12.39697","DOIUrl":null,"url":null,"abstract":"Affected by the global COVID-19 epidemic, many universities in China have to carry out online experimental teaching. Online experimental teaching can fully realize retention of experimental teaching data, the maximum sharing of experimental teaching, and improve teachers’ ability to complete experimental teaching by mobile means through good network storage devices. Scientific and systematic evaluation of online experimental teaching quality can promote continuous improvement of online teaching activities, give full play to teachers’ teaching enthusiasm, improve comprehensive training quality of college students, and make online experimental teaching a new trend of experimental teaching reform. Based on existing literature, this study analyzes the factors affecting the quality of online experimental teaching, puts forward evaluation indicators of online experimental teaching quality, and uses support vector machine training evaluation system to establish evaluation model of online experimental teaching quality in colleges and universities. Experimental results show that evaluation indicator of online experimental teaching quality proposed is relatively perfect, and has good applicability and popularization. The method based on the support vector machine has improved evaluation effect of online experimental teaching quality in colleges and universities. Output evaluation results are highly consistent with actual evaluation results. Online experimental teaching quality evaluation results are very objective and comprehensive. Conclusions have important reference value for online experimental teaching behavior analysis, improvement of online experimental teaching quality evaluation indicators, reduction of online teaching quality evaluation errors, and improvement of online teaching quality evaluation effect.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comprehensive Evaluation of Online Experimental Teaching Quality in Colleges and Universities Based on Support Vector Machine\",\"authors\":\"Jianmeng Ou, Dongdong Lin, Zhitao Zheng\",\"doi\":\"10.3991/ijet.v18i12.39697\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Affected by the global COVID-19 epidemic, many universities in China have to carry out online experimental teaching. Online experimental teaching can fully realize retention of experimental teaching data, the maximum sharing of experimental teaching, and improve teachers’ ability to complete experimental teaching by mobile means through good network storage devices. Scientific and systematic evaluation of online experimental teaching quality can promote continuous improvement of online teaching activities, give full play to teachers’ teaching enthusiasm, improve comprehensive training quality of college students, and make online experimental teaching a new trend of experimental teaching reform. Based on existing literature, this study analyzes the factors affecting the quality of online experimental teaching, puts forward evaluation indicators of online experimental teaching quality, and uses support vector machine training evaluation system to establish evaluation model of online experimental teaching quality in colleges and universities. Experimental results show that evaluation indicator of online experimental teaching quality proposed is relatively perfect, and has good applicability and popularization. The method based on the support vector machine has improved evaluation effect of online experimental teaching quality in colleges and universities. Output evaluation results are highly consistent with actual evaluation results. Online experimental teaching quality evaluation results are very objective and comprehensive. Conclusions have important reference value for online experimental teaching behavior analysis, improvement of online experimental teaching quality evaluation indicators, reduction of online teaching quality evaluation errors, and improvement of online teaching quality evaluation effect.\",\"PeriodicalId\":47933,\"journal\":{\"name\":\"International Journal of Emerging Technologies in Learning\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Emerging Technologies in Learning\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3991/ijet.v18i12.39697\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Emerging Technologies in Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3991/ijet.v18i12.39697","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
Comprehensive Evaluation of Online Experimental Teaching Quality in Colleges and Universities Based on Support Vector Machine
Affected by the global COVID-19 epidemic, many universities in China have to carry out online experimental teaching. Online experimental teaching can fully realize retention of experimental teaching data, the maximum sharing of experimental teaching, and improve teachers’ ability to complete experimental teaching by mobile means through good network storage devices. Scientific and systematic evaluation of online experimental teaching quality can promote continuous improvement of online teaching activities, give full play to teachers’ teaching enthusiasm, improve comprehensive training quality of college students, and make online experimental teaching a new trend of experimental teaching reform. Based on existing literature, this study analyzes the factors affecting the quality of online experimental teaching, puts forward evaluation indicators of online experimental teaching quality, and uses support vector machine training evaluation system to establish evaluation model of online experimental teaching quality in colleges and universities. Experimental results show that evaluation indicator of online experimental teaching quality proposed is relatively perfect, and has good applicability and popularization. The method based on the support vector machine has improved evaluation effect of online experimental teaching quality in colleges and universities. Output evaluation results are highly consistent with actual evaluation results. Online experimental teaching quality evaluation results are very objective and comprehensive. Conclusions have important reference value for online experimental teaching behavior analysis, improvement of online experimental teaching quality evaluation indicators, reduction of online teaching quality evaluation errors, and improvement of online teaching quality evaluation effect.
期刊介绍:
This interdisciplinary journal focuses on the exchange of relevant trends and research results and presents practical experiences gained while developing and testing elements of technology enhanced learning. It bridges the gap between pure academic research journals and more practical publications. So it covers the full range from research, application development to experience reports and product descriptions. Fields of interest include, but are not limited to: -Software / Distributed Systems -Knowledge Management -Semantic Web -MashUp Technologies -Platforms and Content Authoring -New Learning Models and Applications -Pedagogical and Psychological Issues -Trust / Security -Internet Applications -Networked Tools -Mobile / wireless -Electronics -Visualisation -Bio- / Neuroinformatics -Language /Speech -Collaboration Tools / Collaborative Networks