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

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

doi:10.1007/s10639-022-11289-w

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

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

Authors

Julie Vaiopoulou^{1

2}, Stamatios Papadakis¹, Eirini Sifaki³, Michail Kalogiannakis¹, Dimitrios Stamovlasis⁴

Affiliations

¹ Faculty of Education, Department of Preschool Education, University of Crete, Rethymno, Greece.
² Department of Education, University of Nicosia, Nicosia, Cyprus.
³ School of Humanities and Social Sciences, Department of Language & Intercultural Studies, University of Thessaly, Volos, Greece.
⁴ Department of Philosophy and Education, Aristotle University of Thessaloniki, Thessaloniki, Greece.

Abstract

This study explored certain popular educational apps' vital characteristics and potential profiles (n1 = 50) for kindergarten kids. The profile analysis involved a categorization ascended from an evaluation process conducted by pre-service early childhood teachers' (n2 = 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.

Keywords: Classification; Educational apps; Evaluation; Higher education; Latent class analysis; Security.

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