Can AI Robot Teaching Improve Children's Performance in Housework? A Quasi-Experimental Study.
Background: The primary objective of this study is to explore the effects of using Artificial Intelligence (AI) robot-assisted instruction in preschool activities on young children's performance in housework. Methods: A quasi-experimental design was employed, with an experimental group and two contr...
| Publicado en: | Children Vol. 11; no. 11; pp. 1330 - 1340 |
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| Autores principales: | , |
| Formato: | clinical trial pictorial research tables/charts Journal Article |
| Publicado: |
MDPI
Nov2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=181162989&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 181162989 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 22279067 LW6K jtl: Children issn: 22279067 maglogo: N pubinfo: dt: Nov2024 vid: 11 iid: 11 pid: 97109 pub: MDPI artinfo: ui: 181162989 181162989 181162989 10.3390/children11111330 181162989 ppf: 1330 ppct: 10 formats: tig: atl: Can AI Robot Teaching Improve Children's Performance in Housework? A Quasi-Experimental Study. aug: au: Lee, Ching-Fen Tang, Shain-May affil: Department of Early Childhood Education and Care, Minghsin University of Science and Technology, Hsinchu County 304001, Taiwan sug: subj: Artificial Intelligence Robotics Teaching Methods In Infancy and Childhood Home Maintenance In Infancy and Childhood Task Performance and Analysis Human Taiwan Funding Source Male Female Child Adolescence Quasi-Experimental Studies Clinical Trials Content Validity External Validity Pretest-Posttest Control Group Design Questionnaires Surveys Descriptive Statistics Skill Acquisition Motivation Learning Behavior Child: 6-12 years Adolescent: 13-18 years Male Female ab: Background: The primary objective of this study is to explore the effects of using Artificial Intelligence (AI) robot-assisted instruction in preschool activities on young children's performance in housework. Methods: A quasi-experimental design was employed, with an experimental group and two control groups, to observe changes in children's performance in housework before and after AI robot-assisted teaching. The study sample consisted of preschoolers from metropolitan Taipei, with 65 children in the experimental group, 53 in control group 1, and 75 in control group 2. Children participating in the research project required consent from the school, teachers, and parents. The children in the experimental group received AI robot-assisted instruction on household tasks for two days a week over three consecutive weeks, with each session lasting approximately 20–30 min. Control group 1 did not receive any experimental treatment, while control group 2 underwent the same learning schedule and content as the experimental group but was instructed by teachers instead of AI robots. The data were analyzed based on pre- and post-test surveys of parents observing their children's performance in household tasks. Results: This study found that both AI robot-assisted teaching and teacher-led instruction enhanced children's household skills, with the AI robot-assisted method showing slightly better results. These findings suggest that both technological tools and teacher guidance can effectively improve children's housework performance, while artificial intelligence robots may provide young children with motivation and curiosity to learn due to their appearance and interactive design, which deserves further analysis. Conclusion: As technology rapidly advances, young children are exposed to various technological devices at an early age. Integrating technological media into future preschool teaching is inevitable, and leveraging tools like AI robots to support teaching, reduce teacher burden, and diversify instructional methods could be a direction worth considering. pubtype: Academic Journal doctype: clinical trial pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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