Cognitive domains such as Executive Functions (EF) play a critical role in children's school readiness and success (Ng et al., 2015). One of the cognitive variables that assess the quality of school readiness of preschool children is EF.  EF "refers to domain-general cognitive processes that support problem-solving, self-management, and goal-directed behaviour" (Camerota et al., 2018, p. 322). Although there are several definitions of EF, researchers agree that EF consists of three skills; working memory, inhibition, and cognitive flexibility (Diamond & Ling, 2019).

Although cultural influence on EF has attracted a lot of comparative studies (Schirmbeck et al., 2020), few studies have compared countries from sub-Saharan Africa and Europe. Additionally, the majority of cross-national comparisons have used performance-based measures of EF. As opposed to performance-based measures that assess cognitive abilities, the rating scales measure the utilisation of these cognitive skills in a school or at home. Consequently, some authors have reported that ratings and performance-based measures have low correlations (e.g. Camerota, 2018; Catale et al., 2015), signifying they tap different cognitive levels, algorithmic and reflective (Toplak et al., 2013). A measure used across countries is the Childhood Executive Functioning Inventory (CHEXI; Thorell & Nyberg, 2008). The CHEXI assess four latent factors: working memory, planning, regulation, and inhibition. However, the validation of the CHEXI reduced the four factors to two working memory and Inhibition (Thorell et al., 2013).

Several cross-national studies have featured preschool children and have utilised direct assessments to ascertain EF (e.g., Tran et al., 2019). Cook et al., 2019 compared peers with low SES in South Africa and high SES in Australia. Children from South Africa outperformed children in Australia in 2 out of the three EF tasks. Also, children from China outperformed their peers from the US on EF tasks, which was associated with Confucian philosophy (Sabbagh et al., 2006). Other studies based on the CHEXI have reported similar results. For example, Swedish children emerged the best when they were compared with Spain, China and Iran(Thorell et al. 2013). These studies indicate that environment and contextual issues affect EF development.

Hungary's early childhood education is unique in different ways: (1) It has advanced childcare and education for learners aged 3-8 years that is comparable to Norway, Finland and Germany; (2) teachers are highly qualified with a minimum qualification of an undergraduate degree; (3) provides access for disadvantaged students, and (4) enhanced assessment system (Józsa, 2016). Furthermore, the curriculum emphasises children's ability to think, imagine, and focus on science and art. On the other hand, Kenya is now implementing a Competency-Based Curriculum (CBC) to develop individual learners' potential in a holistic and integrated manner while producing intellectually, emotionally, and physically balanced citizens (Republic of Kenya, 2017). In addition, Hungary and Kenya have a devolved system of Government where early childhood education is domiciled. Therefore, cross-national comparisons provide an avenue to investigate the effects of culture, family structure, educational curriculum, government organisation, social values and norms on child development in the two regions (Schirmbeck et al., 2021). Overall, the CHEXI represents a valuable screening tool for predicting academic difficulties (Thorell et al., 2013) and ADHD (Thorell & Nyberg, 2008) due to poor EF, which is critical during the school readiness preparations that form the focus of this study.

The current study had three objectives; (i) To assess EF in Hungarian and Kenyan samples nested in classrooms. (ii) To compare and contrast the similarities and differences of EF skills observed in the two countries. (iii) to offer suggestions to bridge the gaps between the two countries and enhance EF in children.

We sampled 187 preschool children in Hungary, 4 to 8 years (M=6.29 years, SD = 1.18; 78 (46.7%) girls and 420 children aged between 4 to 8 years (M = 7.33 years, SD = .69 boys, 224 (53.3%) girls) from Kenya. Preschool teachers rated EF difficulties using the Childhood Executive Functioning Inventory (CHEXI: Thorell & Nyberg, 2008). To determine the measurement model of the CHEXI, we used Confirmatory Factor Analysis (CFA) to construct the latent factors for the Hungarian and Kenyan samples in AMOS 24. Two factor model according to the theory fitted well with our data, Hungarian sample CMIN/DF of 3.08, CFI = 0.93, SRMR = 0.048 and RMSEA = 0.073, and Kenyan sample CMIN/DF= 2.97, CFI = 0.95, SRMR = 0.0438 and RMSEA = 0.055(Schreiber et al., 2006). We reduced these results to two latent inhibition factors with 11 variables and working memory with 13 variables. To test the group measurement invariance of the CHEXI across the Hungarian and Kenyan cultural groups, the factor analytic approach was used (Milfont & Fischer, 2010). We used Multi-level analysis and linear mixed-effects models based on maximum likelihood estimations (Twisk, 2006) to examine the differences in EF skills between Hungarian and Kenyan Children nested in schools (Hungary 8 and Kenya 27). We identified significant differences in age between Hungary and Kenya, t (604) = -14.92, p < 0.001. Additionally, there was a higher percentage of Kenyan boys than in the Hungarian sample, t(604) = -2.59, p <0.01. Due to these differences, we treated age and gender as control variables in all the multi-level analyses. Since students were nested in classes, classrooms were treated as level two variables. Inhibition, working memory and total EF were treated as the dependent variable. The two countries (Hungary and Kenya) and the interaction term (Region and Age) were treated as the independent variables(Schirmbeck et al., 2021).

Muliti-level analysis showed that Working memory had significant main effect of age at F (1,605) = 169.53, p < .001 and gender at F (1,605) = 6.229, p < 0.013. A significant effect was also noted for the children’s country of origin calculated at F (1,605) = 169.53, p = .021 after controlling for age and gender. For inhibition the significant main effect of age at F (1,605) = 169.53, p < 0.001 and gender computed at F (1,605) = 4.554, p = 0.033. No significant effect was found for the children’s country of origin: F (1,605) = .275, p =.600). The Country x Age interaction was also not significant: F (1,605) = .063 p = .802. For total EF difficulties displayed a significant main effect of age at F (1,605) = 11.60, p < 0.001 and gender at F (1,605) = 11.09, p < 0.001. No significant effect was observed for the children’s country of origin: F (1,605) = .021, p = 0.886. The Country x Age interaction was also not significant: F (1,605) = .322, p = .808. Country of origin had a significant effect on working memory difficulties only but not inhibition and total EF difficulties. Children in Hungary were better at working memory development compared to Kenyan children. However, age and gender had significant main effects on the development of EF across the two countries. Promising EF enhancement interventions embed EF strategies into daily class activities. Such strategies include martial arts and curricula that train for diverse EF skills and daily practice (Blair & Raver, 2015). In addition, indirect strategies that improve sleep and increase joy, social cohesiveness, physical fitness, and social support ameliorate EF (Diamond & Ling, 2016). Such elements are more prevalent in the Hungarian preschool system than in the Kenyan structure.

Amukune, S. (2021). Preschool Education in Finland and Kenya: Comparison within perspectives of Educational Quality. International Journal of Early Childhood Learning, 28(2), 51–67. https://doi.org/10.18848/2327-7939/CGP/v28i02/51-67 Camerota, M., Willoughby, M. T., Kuhn, L. J., & Blair, C. B. (2018). The Childhood Executive Functioning Inventory (CHEXI): Factor structure, measurement invariance, and correlates in US preschoolers. Child Neuropsychology, 24(3), 322–337. Jozsa, K., Barrett, K. C., & Morgan, G. A. (2017). Game-like Tablet Assessment of Approaches to Learning: Assessing Mastery Motivation and Executive Functions. ELECTRONIC JOURNAL OF RESEARCH IN EDUCATIONAL PSYCHOLOGY, 15(3), 665–695. https://doi.org/10.14204/ejrep.43.17026 Ng, F. F.-Y., Tamis-LeMonda, C., Yoshikawa, H., & Sze, I. N.-L. (2015). Inhibitory control in preschool predicts early math skills in first grade: Evidence from an ethnically diverse sample. International Journal of Behavioral Development, 39(2), 139–149. https://doi.org/10.1177/0165025414538558 Republic of Kenya. (2017). Basic Curriculum Framework (p. 147). Kenya Institute of Curriculum Development(KICD). www.kicd.go.ke Schirmbeck, K., Rao, N., & Maehler, C. (2020). Similarities and differences across countries in the development of executive functions in children: A systematic review. Infant and Child Development, 29(1), e2164. Schirmbeck, K., Rao, N., Wang, R., Richards, B., Chan, S. W. Y., & Maehler, C. (2021). Contrasting executive function development among primary school children from Hong Kong and Germany. European Journal of Psychology of Education, 36(4), 923–943. https://doi.org/10.1007/s10212-020-00519-9 Thorell, L. B., & Nyberg, L. (2008). The Childhood Executive Functioning Inventory (CHEXI): A new rating instrument for parents and teachers. Developmental Neuropsychology, 33(4), 536–552. Toplak, M. E., West, R. F., & Stanovich, K. E. (2013). Practitioner review: Do performance‐based measures and ratings of executive function assess the same construct? Journal of Child Psychology and Psychiatry, 54(2), 131–143. Twisk, J. W. R. (2006). Applied Multilevel Analysis: A Practical Guide. Cambridge University Press. https://doi.org/10.1017/CBO9780511610806