{"title":"Literature review of the reciprocal value of artificial and human intelligence in early childhood education","authors":"Lucrezia Crescenzi-Lanna","doi":"10.1080/15391523.2022.2128480","DOIUrl":null,"url":null,"abstract":"Abstract This paper presents a systematic literature review of artificial intelligence (AI)-supported teaching and learning in early childhood. The focus is on human–machine cooperation in education. International evidence and associated problems with the reciprocal contributions of humans and machines are presented and discussed, as well as future horizons regarding AI research in early education. Also, the ethical implications of applying machine learning, deep learning and learning analytics in early childhood education are considered. The method adopted has five steps: identification of the research, evaluation and selection of the literature, data extraction, synthesis, and results. The results shown that AI applications still present limitations in terms of the challenges encountered in early childhood education and data privacy and protection policies.","PeriodicalId":47444,"journal":{"name":"Journal of Research on Technology in Education","volume":"55 1","pages":"21 - 33"},"PeriodicalIF":5.1000,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Research on Technology in Education","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1080/15391523.2022.2128480","RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 1
Abstract
Abstract This paper presents a systematic literature review of artificial intelligence (AI)-supported teaching and learning in early childhood. The focus is on human–machine cooperation in education. International evidence and associated problems with the reciprocal contributions of humans and machines are presented and discussed, as well as future horizons regarding AI research in early education. Also, the ethical implications of applying machine learning, deep learning and learning analytics in early childhood education are considered. The method adopted has five steps: identification of the research, evaluation and selection of the literature, data extraction, synthesis, and results. The results shown that AI applications still present limitations in terms of the challenges encountered in early childhood education and data privacy and protection policies.
期刊介绍:
The Journal of Research on Technology in Education (JRTE) is a premier source for high-quality, peer-reviewed research that defines the state of the art, and future horizons, of teaching and learning with technology. The terms "education" and "technology" are broadly defined. Education is inclusive of formal educational environments ranging from PK-12 to higher education, and informal learning environments, such as museums, community centers, and after-school programs. Technology refers to both software and hardware innovations, and more broadly, the application of technological processes to education.