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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.

The introduction of STEM education, and specifically the implementation of educational robotics (ER), has drawn researchers' attention and has shown that teachers play a crucial role in leading this innovation. The present study concerns in-service and pre-service early childhood teachers, focusing on their perceptions and attitudes about ER use in daily teaching practice. The data were collected via a questionnaire (N = 201) and explored using latent class analysis, which detected distinct clusters/profiles of participants based on their pattern of responses. Two clusters were identified: Cluster1 was relatively homogeneous, including those who share a positive attitude towards ER, while Cluster2 was heterogeneous, comprising participants with inconsistent responses and expressing negative and skeptical thinking. The cluster memberships were associated with external covariates, such as age, years of teaching experience, and variables measuring their technological competencies. The results showed that teaching experience and age were negatively associated with cluster1-membership, while educational robotics knowledge was positively associated. The findings are interpretable, and the implications for education are discussed considering the current literature.

In the last decade, interactive touchscreen devices have become ubiquitous in young children, and toddlers first experience touchscreen technology before two. Although parents have a vital role in developing the home environment as a stimulus for development, they also have conflicting views on the appropriateness of using apps to deliver educational content for assorted reasons. The purpose of the study was to reveal various aspects of children's smart mobile use at home, such as the frequency of mobile device usage, preferred app types, and parent beliefs and strategies. Three hundred twenty-five parents of kindergarten children took part in this study. The present study revealed that parents seek to support their children's learning at home via mobile devices. Furthermore, parents lack knowledge about app developmentally appropriateness and need further guidance. We expect the findings to serve as a reference for researchers to better information for parents and create apps with real educational value for children.

The present study aimed to assess the effect of two different types of digital technologies (computers and tablets) in early childhood students' understanding of numbers. Three hundred and sixty-five children (mean age in months, M = 62.0, SD = 5.5) from 21 kindergarten classes were randomly assigned to two intervention groups and a business-as-usual control group. The interventions were conducted over 24 half-hour lessons. Data was collected during the 2013-2014 school year using a three-step research procedure. Students' knowledge about numbers was assessed using the Test of Early Mathematics Ability-3 (TEMA-3). Findings were that (a) both experimental groups significantly outperformed the control group on the posttest, (b) the group that used tablet computers significantly outperformed the group that used personal computers on the posttest, and (c) there was no significant difference between genders on the posttest. Our findings support that computers and especially tablets, when combined with the use of developmentally appropriate software into the children's daily routines, may provide a substantial contribution to early childhood students' comprehension of numbers.

As the introduction of natural sciences in early childhood education differs from natural sciences for adults, planning appropriate activities for preschool is a delicate task with various dimensions and parameters. Teaching natural sciences in kindergarten can be a complex procedure which combines exploring and comprehending children's perceptions, scientific content and the learning environment. Magnetism, which is very attractive subject for young children, is a commonly negotiated topic at the preschool level. In this paper, we present an empirical case study that examines whether the picture story reading method can be beneficial for young children learning about magnetism. Findings underline the importance of drawing on a variety of evidence in assessing young children's understanding of magnets.

The present study investigates and compares the influence of teaching Realistic Mathematics on the development of mathematical competence in kindergarten. The sample consisted of 231 Greek kindergarten students. For the implementation of the survey, we conducted an intervention, which included one experimental and one control group. Children in the experimental group were taught Realistic Mathematics according to the principles of Realistic Mathematics Education. The control group was taught mathematics following the basic pedagogical principles of curriculum for kindergarten students. In order to evaluate the mathematical performance of children we used the Test of Early Mathematics Ability (TEMA-3). The results showed that the teaching technique with the use of Realistic Mathematic Education contributed significantly to the development of mathematical competence of young children. Moreover, factors such as gender, age and nonverbal cognitive ability, did not seem to differentiate the development of mathematical competence of children.

As artificial intelligence (AI) becomes increasingly prevalent, it has become a topic of interest in education. The use of AI in education poses complex issues, not only in terms of its impact on teaching and learning outcomes but also in terms of the ethical considerations regarding personal data and the individual needs of each student. Our study systematically analyzed empirical research on the use of AI in primary education, specifically for children aged 4–12 years old. We reviewed 35 articles indexed in SCOPUS, filtered them according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, analyzed them, and categorized the findings. The research focused on the studies' objectives, learning content, learning outcomes, learning activities, and the pedagogy of activities or the AI tools. Our categorization resulted in three main categories of research objectives regarding the creation, implementation, and evaluation of AI tools and five categories for learning content: AI and ML (machine learning) concepts in STEM and STEAM, language learning, mathematics, arts, and various other subjects. The learning activities were split into four categories: apply, engage, interact, use; project-based learning with multiple activities; experience and practice; and students as tutors. The learning outcomes were split into three levels: cognitive, affective, and psychomotor. The pedagogy of AI tools falls into four categories: constructivism, experiential learning, AI-assisted learning, and project-based learning. The implications for teacher professional development are discussed. [ABSTRACT FROM AUTHOR]