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幼儿教育应用程序的分类与评估:安全至关重要。

Classification and evaluation of educational apps for early childhood: Security matters.

作者信息

Vaiopoulou Julie, Papadakis Stamatios, Sifaki Eirini, Kalogiannakis Michail, Stamovlasis Dimitrios

机构信息

Faculty of Education, Department of Preschool Education, University of Crete, Rethymno, Greece.

Department of Education, University of Nicosia, Nicosia, Cyprus.

出版信息

Educ Inf Technol (Dordr). 2023;28(3):2547-2578. doi: 10.1007/s10639-022-11289-w. Epub 2022 Aug 24.

DOI:10.1007/s10639-022-11289-w
PMID:36035974
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9398896/
Abstract

This study explored certain popular educational apps' vital characteristics and potential profiles ( 50) for kindergarten kids. The profile analysis involved a categorization ascended from an evaluation process conducted by pre-service early childhood teachers' ( 295) at the University of Crete, Greece, using a new instrument, validated in the present research, the ETEA-2 scale. The categorization criteria were the five dimensions of the ETEA-2: Learning, Suitability, Usability, Security, and Parental Control. The classification based on Latent Class Analysis led to three apps' profiles: Cluster/profile 1 includes apps that have high values in Learning, Usability, Suitability, and medium Parental Control and Security; Cluster/Profile 2 includes apps with medium Learning, Usability, Suitability, but low Parental Control and High Security; Cluster/Profile 3 includes apps with medium Learning, Usability, Suitability, but low Parental Control and low Security. This profile scheme is an indicative categorization summarizing the crucial features that popular apps possess and can help parents and/or educators' decision-making on choosing the desirable application for their kids. Moreover, from an independent evaluation of these specific fifty apps sought on the internet, the members of Cluster2/Profile 2 were the most popular and preferable, as suggested by the number of downloads. This profile is distinguished for the security dimension.

摘要

本研究探讨了某些流行的教育应用程序对幼儿园儿童的重要特征和潜在概况(50个)。概况分析涉及从希腊克里特大学学前教育职前教师(295名)使用一种新工具进行的评估过程中进行的分类,该工具在本研究中得到验证,即ETEA - 2量表。分类标准是ETEA - 2的五个维度:学习、适用性、可用性、安全性和家长控制。基于潜在类别分析的分类产生了三种应用程序概况:集群/概况1包括在学习、可用性、适用性方面具有高价值,家长控制和安全性中等的应用程序;集群/概况2包括学习、可用性、适用性中等,但家长控制低且安全性高的应用程序;集群/概况3包括学习、可用性、适用性中等,但家长控制低且安全性低的应用程序。这种概况方案是一种指示性分类,总结了流行应用程序所具有的关键特征,可以帮助家长和/或教育工作者在为孩子选择理想应用程序时做出决策。此外,从对在互联网上搜索到的这五十个特定应用程序的独立评估来看,集群2/概况2中的应用程序是最受欢迎和最可取的,下载量表明了这一点。这个概况在安全维度上很突出。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c81f/9398896/c99c8f5bd348/10639_2022_11289_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c81f/9398896/e0dcf0aa1939/10639_2022_11289_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c81f/9398896/2616051cf736/10639_2022_11289_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c81f/9398896/c99c8f5bd348/10639_2022_11289_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c81f/9398896/e0dcf0aa1939/10639_2022_11289_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c81f/9398896/2616051cf736/10639_2022_11289_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c81f/9398896/c99c8f5bd348/10639_2022_11289_Fig3_HTML.jpg

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Developing numeracy skills using interactive technology in a play-based learning environment.在基于游戏的学习环境中使用交互式技术培养算术技能。
Int J STEM Educ. 2018;5(1):39. doi: 10.1186/s40594-018-0135-2. Epub 2018 Oct 11.
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Illustration of Step-Wise Latent Class Modeling With Covariates and Taxometric Analysis in Research Probing Children's Mental Models in Learning Sciences.
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Front Psychol. 2022 Oct 20;13:975515. doi: 10.3389/fpsyg.2022.975515. eCollection 2022.
在学习科学中探究儿童心理模型的研究中,带有协变量的逐步潜在类别建模及分类分析的图示。
Front Psychol. 2018 Apr 16;9:532. doi: 10.3389/fpsyg.2018.00532. eCollection 2018.
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Exposure and Use of Mobile Media Devices by Young Children.幼儿接触和使用移动媒体设备的情况。
Pediatrics. 2015 Dec;136(6):1044-50. doi: 10.1542/peds.2015-2151. Epub 2015 Nov 2.
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