Early artificial intelligence education: Effects of cooperative play and direct instruction on kindergarteners' computational thinking, sequencing, self‐regulation and theory of mind skills.
Background: While the integration of robot‐based learning in early childhood education has gained increasing attention in recent years, there is still a lack of evidence regarding the impact of AI robots on young children's learning. Objectives: The study explored the effectiveness of two AI educati...
| Publicado en: | Journal of Computer Assisted Learning Vol. 40; no. 6; pp. 2917 - 2926 |
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| Autores principales: | , , , , |
| Formato: | pictorial research tables/charts randomized controlled trial Journal Article |
| Publicado: |
Wiley-Blackwell
Dec2024
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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=180899672&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 180899672 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Dec2024 vid: 40 iid: 6 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 180899672 178669860 180899672 180899672 10.1111/jcal.13040 180899672 ppf: 2917 ppct: 9 formats: tig: atl: Early artificial intelligence education: Effects of cooperative play and direct instruction on kindergarteners' computational thinking, sequencing, self‐regulation and theory of mind skills. aug: au: Su, Jiahong Yang, Weipeng Yim, Iris Heung Yue Li, Hui Hu, Xiao affil: Faculty of Education, The University of Hong Kong, Hong Kong, China sug: subj: Artificial Intelligence Education Students, Elementary Thinking Play and Playthings Self Regulation Theory of Mind Problem Solving Outcomes of Education Human China Female Male Child Randomized Controlled Trials Random Assignment Control Group Pretest-Posttest Control Group Design Time Factors Comparative Studies One-Way Analysis of Variance T-Tests Data Analysis Software Descriptive Statistics Learning Methods Robotics Child: 6-12 years Female Male ab: Background: While the integration of robot‐based learning in early childhood education has gained increasing attention in recent years, there is still a lack of evidence regarding the impact of AI robots on young children's learning. Objectives: The study explored the effectiveness of two AI education approaches in advancing kindergarteners' computational thinking, sequencing, self‐regulation and theory of mind skills. Methods: An experiment was conducted with 90 kindergarteners (ages 5–6) randomly assigned to either a direct instruction (DI), cooperative play (CP) or control group. Results: Results show that (1) children in all three groups had significant improvements on computational thinking, sequencing and self‐regulation; (2) both early AI education approaches (CP and DI) significantly enhance young children's computational thinking, sequencing, self‐regulation and theory of mind skills; (3) the DI group had significant higher improvement than the CP group on computational thinking; (4) the CP group exhibited greater enhancements in theory of mind skills than the DI group. Conclusion: These findings jointly demonstrate that each AI educational approach has unique strengths, underscoring the significance of designing new pedagogies to expand children's skills. Lay Description: What is already known about this topic?: Artificial intelligence (AI) has become an integral part of the modern world.The integration of robot‐based learning in early childhood education has gained increasing attention in recent years. What this paper adds?: The aim of this study was to investigate the contribution of an AI robot for promoting computational thinking, sequencing, self‐regulation and theory of mind skills of kindergarten children.The study explored the effectiveness of two AI education approaches in advancing kindergarteners' computational thinking, sequencing, self‐regulation and theory of mind skills. Implications for practice and/or policy: These findings jointly demonstrate that each AI educational approach has unique strengths, underscoring the significance of designing new pedagogies to expand children's skills.The conclusions drawn from this research carry weighty implications, encouraging educators and research scholars to traverse new pathways for cultivating crucial competencies in young children, leveraging the power of early AI education. pubtype: Academic Journal doctype: pictorial research tables/charts randomized controlled trial Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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