{"title":"Effect of students’ deep learning in virtual venue environment: a meta-analysis based on 45 experiments and quasi-experiments at home and abroad","authors":"Xinyi Wu, Xiaohui Chen, Xingyang Wang, Hanxi Wang","doi":"10.1007/s10639-024-12985-5","DOIUrl":null,"url":null,"abstract":"<p>With the application of virtual venues in the field of education, numerous educational empirical studies have examined the impact of deep learning in the learning environment of virtual venues, but the conclusions are not always in agreement. The present study adopted the meta-analysis method and RStudio software to test the overall effect of 45 domestic and foreign experimental and quasi-experimental studies, and eight moderating variables (experiment period, knowledge type, virtual venue type, and feedback strategy) were analyzed. The research results indicated that moderating variables had different degrees of influence on the deep learning effect of students in the learning environment of virtual venues. There were no intra-group differences in the type of virtual venue and the experiment period, while there were intra-group differences in other moderating variables. According to the results of meta-analysis, suggestions were put forward from four aspects (course design of virtual venues, selection and application of feedback strategies, knowledge type design of virtual venues, and empirical research suggestions) to serve as references for strengthening the deep learning impact of students and the scientific design of course content of virtual venues.</p>","PeriodicalId":51494,"journal":{"name":"Education and Information Technologies","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Education and Information Technologies","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1007/s10639-024-12985-5","RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0
Abstract
With the application of virtual venues in the field of education, numerous educational empirical studies have examined the impact of deep learning in the learning environment of virtual venues, but the conclusions are not always in agreement. The present study adopted the meta-analysis method and RStudio software to test the overall effect of 45 domestic and foreign experimental and quasi-experimental studies, and eight moderating variables (experiment period, knowledge type, virtual venue type, and feedback strategy) were analyzed. The research results indicated that moderating variables had different degrees of influence on the deep learning effect of students in the learning environment of virtual venues. There were no intra-group differences in the type of virtual venue and the experiment period, while there were intra-group differences in other moderating variables. According to the results of meta-analysis, suggestions were put forward from four aspects (course design of virtual venues, selection and application of feedback strategies, knowledge type design of virtual venues, and empirical research suggestions) to serve as references for strengthening the deep learning impact of students and the scientific design of course content of virtual venues.
期刊介绍：
The Journal of Education and Information Technologies (EAIT) is a platform for the range of debates and issues in the field of Computing Education as well as the many uses of information and communication technology (ICT) across many educational subjects and sectors. It probes the use of computing to improve education and learning in a variety of settings, platforms and environments.
The journal aims to provide perspectives at all levels, from the micro level of specific pedagogical approaches in Computing Education and applications or instances of use in classrooms, to macro concerns of national policies and major projects; from pre-school classes to adults in tertiary institutions; from teachers and administrators to researchers and designers; from institutions to online and lifelong learning. The journal is embedded in the research and practice of professionals within the contemporary global context and its breadth and scope encourage debate on fundamental issues at all levels and from different research paradigms and learning theories. The journal does not proselytize on behalf of the technologies (whether they be mobile, desktop, interactive, virtual, games-based or learning management systems) but rather provokes debate on all the complex relationships within and between computing and education, whether they are in informal or formal settings. It probes state of the art technologies in Computing Education and it also considers the design and evaluation of digital educational artefacts. The journal aims to maintain and expand its international standing by careful selection on merit of the papers submitted, thus providing a credible ongoing forum for debate and scholarly discourse. Special Issues are occasionally published to cover particular issues in depth. EAIT invites readers to submit papers that draw inferences, probe theory and create new knowledge that informs practice, policy and scholarship. Readers are also invited to comment and reflect upon the argument and opinions published. EAIT is the official journal of the Technical Committee on Education of the International Federation for Information Processing (IFIP) in partnership with UNESCO.
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