School readiness is a foundational predictor of long-term academic success and socio-economic mobility. In Djibouti, disparities in early learning outcomes reflect unequal preschool access, household-level differences, and regional disparities in service provision. This research addresses three questions: (1) What are the levels of school readiness across key developmental domains? (2) Which child-, household-, and region-level factors influence school readiness outcomes? (3) How do these outcomes vary across socio-economic and geographic groups? Drawing on data from 1,155 children aged 5-6 assessed through the International Development and Early Learning Assessment (IDELA), this research employs a multilevel mixed-effects model to estimate the effects of preschool attendance, caregiver engagement, and institutional context across four domains: literacy, numeracy, socio-emotional development, and physical development. The conceptual framework integrates Ecological Systems Theory, Human Capital Theory, and the Cumulative Risk Model to examine the interplay between home, school, and structural environments. Preschool attendance is the strongest predictor of literacy outcomes, associated with a 9.05-point gain (p < 0.001). Father’s participation in home literacy adds 2.64 points (p = 0.015), while the presence of a preschool-enrolled sibling contributes 3.92 points (p = 0.018). No statistically significant gender-based differences were found (p = 0.381). Parental education and behavioral engagement show strong positive associations with literacy and numeracy performance. Public school students score lower in numeracy than peers in private institutions (p < 0.05). Regional disparities are substantial. Preschool attendees in Djibouti-Ville score an average of 99.7, compared to 72.9 in Dikhil and 75.6 in Obock. Children in Tadjourah score 6.90 points lower than those in Ali-Sabieh (p = 0.026). Findings highlight the need for integrated policy reforms that expand equitable access, improve instructional quality, and strengthen parental engagement. Data-driven, multisectoral strategies will enhance school readiness and support Djibouti’s broader development goals.
| Published in | International Journal of Elementary Education (Volume 14, Issue 2) |
| DOI | 10.11648/j.ijeedu.20251402.11 |
| Page(s) | 20-38 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2025. Published by Science Publishing Group |
Early Childhood Education, Early Childhood Development, Ecological Systems Theory, Human Capital Theory, Cumulative Risk Model
| [1] | El-Kogali, S., & Krafft, C. (2015). Expanding opportunities for the next generation: Early childhood development in the Middle East and North Africa. World Bank Publications. |
| [2] | Khattab, M. S. (1995). A comprehensive review of the status of early childhood development in the Middle East and North Africa. ERIC. |
| [3] | Hlasny, V. (2017). Evolution of opportunities for early childhood development in Arab countries. International Journal of Human Rights in Healthcare, 10(4), 256-276. |
| [4] | Seife, T. K. (2020). Educational system obstruction consequence in the political volatility: Comparative assessments Somalia and Djibouti. In Educational system obstruction consequence in the political volatility comparative assessments Somalia and Djibouti (pp. 2-25). Springer Nature. |
| [5] | Carr-Hill, R. A., Eshete, A., Sedel, C., & de Souza, A. (2005). The education of nomadic peoples in East Africa: Djibouti, Eritrea, Ethiopia, Kenya, Tanzania and Uganda (Synthesis Report No. 799). African Development Bank. |
| [6] | Djibouti Ministry of National Education and Vocational Training. (2023). Annuaire statistique de l’éducation 2022-2023. MENFOP. |
| [7] | World Bank. (2024). Country climate and development report: Republic of Djibouti. World Bank Publications. |
| [8] | Carr-Hill, R. (2006). Educational services and nomadic groups in Djibouti, Eritrea, Ethiopia, Kenya, Tanzania and Uganda. In The education of nomadic peoples: Current issues, future prospects (pp. 35-52). Berghahn Books. |
| [9] | D’Addio, A. (2024). Regulation and governance of non-state early childhood care and education in African countries. UNESCO. |
| [10] | Yoshikawa, H., & Kabay, S. (2015). The evidence base on early childhood care and education in global contexts. Background paper for the UNESCO 2015 Education for All Global Monitoring Report. |
| [11] | Barnett, W. S., & Lamy, C. E. (2013). Achievement gaps start early: Preschool can help. In P. L. Carter & K. G. Welner (Eds.), Closing the opportunity gap: What America must do to give every child an even chance (pp. 98-110). Oxford University Press. |
| [12] | Heckman, J. J. (2006). Skill formation and the economics of investing in disadvantaged children. Science, 312(5782), 1900-1902. |
| [13] | Duncan, G. J., & Magnuson, K. (2013). Investing in preschool programs. Journal of Economic Perspectives, 27(2), 109-132. |
| [14] | Engle, P. L., Fernald, L. C. H., Alderman, H., Behrman, J. R., O'Gara, C., Yousafzai, A.,... & Iltus, S. (2011). Strategies for reducing inequalities and improving developmental outcomes for young children in low-income and middle-income countries. The Lancet, 378(9799), 1339-1353. |
| [15] | UNICEF. (2019). A world ready to learn: Prioritizing quality early childhood education. United Nations Children’s Fund. |
| [16] | Yoshikawa, H., Weiland, C., Brooks-Gunn, J., Burchinal, M. R., Espinosa, L. M., Gormley, W. T.,... & Zaslow, M. J. (2013). Investing in our future: The evidence base on preschool education. Society for Research in Child Development. |
| [17] | Mullis, I., Martin, M., Foy, P., & Drucker, K. (2012). PIRLS 2011 international results in reading. TIMSS & PIRLS International Study Center, Boston College. |
| [18] | Berlinski, S., & Schady, N. (2015). The early years: Child well-being and the role of public policy. Springer Nature. |
| [19] | Shonkoff, J. P., & Phillips, D. A. (2000). From neurons to neighborhoods: The science of early childhood development. National Academies Press. |
| [20] | Pisani, L., Borisova, I., & Dowd, A. J. (2018). Developing and validating the International Development and Early Learning Assessment (IDELA). International Journal of Educational Research, 91, 1-15. |
| [21] | Heckman, J. J., & Masterov, D. V. (2007). The productivity argument for investing in young children. Early Childhood Research Collaborative Discussion Paper. |
| [22] | Farah, A. I. (2024). Rapid learning for lasting change: Accelerated basic education in post-conflict, Somalia. International Journal of Education, 9(4), 188-202. |
| [23] | Dudzik, D. L. (2008). English policies, curricular reforms, and teacher development in multilingual, postcolonial Djibouti (Doctoral dissertation). University of Minnesota. |
| [24] | UNICEF. (2019). Djibouti country programme document 2018-2022. United Nations Children’s Fund. |
| [25] | Idereh, A. M. (2018). Collaborative community and social development: A study of selected neighborhoods in Djibouti (Doctoral dissertation). Kampala International University, College of Economics and Management. |
| [26] | Shehadeh, H. M. (2008). Approaching the problem of equity, quality and access of early childhood care and education: A descriptive analysis of growth and development in the Arab States (Doctoral dissertation). Seton Hall University. |
| [27] | Ayan, M. I. (2018). Collaborative community and social development: A study of selected neighborhoods in Djibouti (Doctoral dissertation). Kampala International University, College of Economics. |
| [28] | Barnes, V. (2018). Child-centred social work: Theory and practice. Bloomsbury Publishing. |
| [29] | Mollborn, S. (2016). Young children’s developmental ecologies and kindergarten readiness. Demography, 53(6), 1853-1882. |
| [30] | Schoon, I., & Heckhausen, J. (2019). Conceptualizing individual agency in the transition from school to work: A social-ecological developmental perspective. Adolescent Research Review, 4, 135-148. |
| [31] | Currie, J., & Almond, D. (2011). Human capital development before age five. In D. Card & O. Ashenfelter (Eds.), Handbook of labor economics (Vol. 4, pp. 1315-1486). Elsevier. |
| [32] | Johnson, R. C., & Schoeni, R. F. (2011). The influence of early-life events on human capital, health status, and labor market outcomes over the life course. The BE Journal of Economic Analysis & Policy, 11(3). |
| [33] | Kamuli, K. E. (2019). An exploration of drop-in among students who are at risk of dropping out of lower secondary school in Eritrea (Doctoral dissertation). University College London. |
| [34] | Mistry, R. S., Benner, A. D., Biesanz, J. C., Clark, S. L., & Howes, C. (2010). Family and social risk, and parental investments during the early childhood years as predictors of low-income children's school readiness outcomes. Early Childhood Research Quarterly, 25(4), 432-449. |
| [35] | Rodriguez-Escobar, O. L. (2009). Application of the cumulative risk model in predicting school readiness in Head Start children (Doctoral dissertation). |
| [36] | Britto, P. R., Yoshikawa, H., & Boller, K. (2011). Quality of early childhood development programs in global contexts: Rationale for investment, conceptual framework and implications for equity. Social Policy Report, 25(2), 1-31. |
| [37] | Crouch, L., & Merseth, K. A. (2017). The preschool entitlement: A locally adaptable policy instrument to expand and improve preschool education (RTI Press Publication No. OP-0053-1705). RTI International. |
| [38] | McCoy, D. C., Salhi, C., Yoshikawa, H., Black, M. M., Britto, P. R., & Fink, G. (2018). Home- and center-based learning opportunities for preschoolers in low- and middle-income countries. Children and Youth Services Review, 88, 44-56. |
| [39] | Krafft, C. (2015). Increasing educational attainment in Egypt: The impact of early childhood care and education. Economics of Education Review, 46, 127-143. |
| [40] | Winter, S. M., & Kelley, M. F. (2008). Forty years of school readiness research: What have we learned? Childhood Education, 84(5), 260-266. |
| [41] | Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., Pagani, L. S., Feinstein, L., Engel, M., Brooks-Gunn, J., Sexton, H., Duckworth, K., & Japel, C. (2007). School readiness and later achievement. Developmental Psychology, 43(6), 1428-1446. |
| [42] | Black, M. M., Walker, S. P., Fernald, L. C. H., Andersen, C. T., DiGirolamo, A. M., Lu, C., & Grantham-McGregor, S. (2017). Early childhood development coming of age: Science through the life course. The Lancet, 389(10064), 77-90. |
| [43] | Rose, P., & Greeley, M. (2006). Education in fragile states: Capturing lessons and identifying good practice. DAC Fragile States Group. |
| [44] | Browne, D. T., Wade, M., Prime, H., & Jenkins, J. M. (2018). School readiness amongst urban Canadian families: Risk profiles and family mediation. Journal of Educational Psychology, 110(1), 133-146. |
| [45] | Meisels, S. J., & Shonkoff, J. P. (2000). Early childhood intervention: A continuing evolution. In J. P. Shonkoff & S. J. Meisels (Eds.), Handbook of early childhood intervention (2nd ed., pp. 3-31). Cambridge University Press. |
| [46] | Ou, S.-R. (2005). Pathways of long-term effects of an early intervention program on educational attainment: Findings from the Chicago longitudinal study. Journal of Applied Developmental Psychology, 26(5), 578-611. |
| [47] | Glewwe, P. W., Hanushek, E. A., Humpage, S. D., & Ravina, R. (2011). School resources and educational outcomes in developing countries: A review of the literature from 1990 to 2010 (Working Paper No. 17554). National Bureau of Economic Research. |
| [48] | Youssouf, Y. B. (2023). The future of physical education and sports in light of the crisis of playgrounds in schools in the Republic of Djibouti. Journal of Advances in Sports and Physical Education, 6(6), 96-101. |
| [49] | Gorard, S., See, B. H., Siddiqui, N., El Soufi, N., Hitt, L., & Lu, B. (2023). Improving attendance and enrolment at school for children living in poverty. Nordic Journal of Systematic Reviews in Education, 1(1), 1-29. |
| [50] | Kingston, S., Huang, K. Y., Calzada, E., Dawson‐McClure, S., & Brotman, L. (2013). Parent involvement in education as a moderator of family and neighborhood socioeconomic context on school readiness among young children. Journal of Community Psychology, 41(3), 265-276. |
| [51] | Sheridan, S. M., Knoche, L. L., Edwards, C. P., Bovaird, J. A., & Kupzyk, K. A. (2010). Parent engagement and school readiness: Effects of the Getting Ready intervention on preschool children's social-emotional competencies. Early Education and Development, 21(1), 125-156. |
| [52] | Lee, Y., Kim, K., & Yudron, M. (2024). School readiness of immigrant-origin children and enriching experiences. Early Education and Development, 35(6), 1127-1140. |
| [53] | Hibel, J. R. (2009). Divergent academic pathways: Racial/ethnic, national origin, and generational status variation in school readiness, kindergarten through eighth grade academic ability growth, and adolescent academic self-concept (Doctoral dissertation). Pennsylvania State University. |
| [54] | Panlilio, C. C., Harden, B. J., & Harring, J. (2018). School readiness of maltreated preschoolers and later school achievement: The role of emotion regulation, language, and context. Child Abuse & Neglect, 75, 82-91. |
| [55] | Lapointe, V. R., Ford, L., & Zumbo, B. D. (2007). Examining the relationship between neighborhood environment and school readiness for kindergarten children. Early Education and Development, 18(3), 473-495. |
| [56] | Hong, Y., & Zeng, D. (2023). Early and continuing grandparental care and middle school students’ educational and mental health outcomes in China. Journal of Community Psychology, 51(2), 676-694. |
| [57] | McClelland, M. M., Tominey, S. L., Schmitt, S. A., Hatfield, B. E., Purpura, D. J., Gonzales, C. R., & Tracy, A. N. (2019). Red light, purple light! Results of an intervention to promote school readiness for children from low-income backgrounds. Frontiers in Psychology, 10, 2365. |
| [58] | Vijayalakshmi, A., & Jayasudha, M. (2024). Artificial intelligence and data analytics. Academic Guru Publishing House. |
| [59] | Raudenbush, S. W. (1993). A crossed random effects model for unbalanced data with applications in cross-sectional and longitudinal research. Journal of Educational Statistics, 18(4), 321-349. |
| [60] | Cunnings, I., Finlayson, I., & Plonsky, L. (2015). Mixed effects modeling and longitudinal data analysis. In L. Plonsky (Ed.), Advancing quantitative methods in second language research (pp. 159-181). Routledge. |
| [61] | Teshale, A. B., Tesema, G. A., Worku, M. G., Yeshaw, Y., & Tessema, Z. T. (2020). Anemia and its associated factors among women of reproductive age in eastern Africa: A multilevel mixed-effects generalized linear model. PLoS One, 15(9), e0238957. |
| [62] | Grant, E. M., Young, D. R., & Wu, T. T. (2015). Predictors for physical activity in adolescent girls using statistical shrinkage techniques for hierarchical longitudinal mixed effects models. PLoS One, 10(4), e0125431. |
| [63] | Forns, J., Dadvand, P., Foraster, M., Alvarez-Pedrerol, M., Rivas, I., López-Vicente, M.,... & Sunyer, J. (2016). Traffic-related air pollution, noise at school, and behavioral problems in Barcelona schoolchildren: A cross-sectional study. Environmental Health Perspectives, 124(4), 529-535. |
| [64] | Dearden, L., Sibieta, L., & Sylva, K. (2011). The socio-economic gradient in early child outcomes: Evidence from the Millennium Cohort Study. IZA Discussion Paper Series. Retrieved from |
| [65] | Sun, J., Lau, C., Sincovich, A., & Rao, N. (2018). Socioeconomic status and early child development in East Asia and the Pacific: The protective role of parental engagement in learning activities. Children and Youth Services Review, 93, 321-330. |
| [66] | Rao, N., Cohrssen, C., Sun, J., Su, Y., & Perlman, M. (2021). Early child development in low-and middle-income countries: Is it what mothers have or what they do that makes a difference to child outcomes? Advances in Child Development and Behavior, 60, 1-44. |
| [67] | Soto-Ramírez, P., Jiang, H., & Strasser, K. (2022). Early home learning environment profiles and their contribution to child development in Chile. Children and Youth Services Review, 137, 106488. |
| [68] | McGinnity, F., McMullin, P., & Murray, A. (2017). Social inequality in cognitive outcomes in Ireland: What is the role of the home learning environment and childcare? In M. M. Connolly & T. Williams (Eds.), Cherishing all the children equally? Children's economic and social rights (pp. 199-218). Edward Elgar Publishing. |
| [69] | Hindman, A. H., Skibbe, L. E., & Miller, A. (2010). Ecological contexts and early learning: Contributions of child, family, and classroom factors during Head Start to literacy and mathematics growth through first grade. Early Childhood Research Quarterly, 25(2), 235-250. |
| [70] | Rimm-Kaufman, S. E., & Pianta, R. C. (2000). An ecological perspective on the transition to kindergarten: A theoretical framework to guide empirical research. Journal of Applied Developmental Psychology, 21(5), 491-511. |
| [71] | Currie, J., & Almond, D. (2011). Human capital development before age five. In D. Card & O. Ashenfelter (Eds.), Handbook of labor economics (Vol. 4, pp. 1315-1486). Elsevier. |
| [72] | Mistry, R. S., Benner, A. D., Biesanz, J. C., Clark, S. L., & Howes, C. (2010). Family and social risk, and parental investments during the early childhood years as predictors of low-income children's school readiness outcomes. Early Childhood Research Quarterly, 25(4), 432-449. |
| [73] | Heckman, J. J. (2011). The economics of inequality: The value of early childhood education. American Educator, 35(1), 31. |
| [74] | Mollborn, S. (2016). Young children’s developmental ecologies and kindergarten readiness. Demography, 53(6), 1853-1882. |
| [75] | Evans, G. W., Li, D., & Whipple, S. S. (2013). Cumulative risk and child development. Psychological Bulletin, 139(6), 1342-1396. |
| [76] | Pratt, M. E., McClelland, M. M., Swanson, J., & Lipscomb, S. T. (2016). Family risk profiles and school readiness: A person-centered approach. Early Childhood Research Quarterly, 36, 462-474. |
| [77] | Downer, J. T., & Myers, S. S. (2010). Application of a developmental/ecological model to family-school partnerships. In S. L. Christenson & A. L. Reschly (Eds.), Handbook of school-family partnerships (pp. 3-29). Routledge. |
| [78] | Grabowski, L. J., Schabo, K. T., & Mortimer, J. T. (2001). Global and economic self-efficacy in the educational attainment process. Social Psychology Quarterly, 64(2), 164-179. |
| [79] | World Bank. (2018). World development report 2018: Learning to realize education’s promise. Washington, DC: World Bank. |
| [80] | Mwaura, P. A., Sylva, K., & Malmberg, L. E. (2008). Evaluating the Madrasa preschool programme in East Africa: A quasi‐experimental study. International Journal of Early Years Education, 16(3), 237-255. |
| [81] | Garcia, M. H., Pence, A., & Evans, J. (Eds.). (2008). Africa’s future, Africa’s challenge: Early childhood care and development in Sub-Saharan Africa. Washington, DC: World Bank Publications. |
| [82] | Su, Y., Lau, C., & Rao, N. (2020). Early education policy in China: Reducing regional and socioeconomic disparities in preschool attendance. Early Childhood Research Quarterly, 53, 11-22. |
| [83] | Grace, R., Bowes, J., & Elcombe, E. (2014). Child participation and family engagement with early childhood education and care services in disadvantaged Australian communities. International Journal of Early Childhood, 46(3), 271-298. |
| [84] | Markowitz, A. J., Bassok, D., & Grissom, J. A. (2020). Teacher-child racial/ethnic match and parental engagement with Head Start. American Educational Research Journal, 57(5), 2132-2174. |
| [85] | Barnett, M. A., Paschall, K. W., Mastergeorge, A. M., Cutshaw, C. A., & Warren, S. M. (2020). Influences of parent engagement in early childhood education centers and the home on kindergarten school readiness. Early Childhood Research Quarterly, 53, 260-273. |
| [86] | Pilarz, A. R., Lin, Y. C., & Premo, E. M. (2024). Family engagement practices and children’s attendance and early learning skills in a public pre-kindergarten program. Children and Youth Services Review, 163, 107794. |
APA Style
Ba, A., Barre, M. B. (2025). Determinants of Children's Preparedness for Primary Education in Djibouti: An Empirical Analysis Using IDELA Assessment. International Journal of Elementary Education, 14(2), 20-38. https://doi.org/10.11648/j.ijeedu.20251402.11
ACS Style
Ba, A.; Barre, M. B. Determinants of Children's Preparedness for Primary Education in Djibouti: An Empirical Analysis Using IDELA Assessment. Int. J. Elem. Educ. 2025, 14(2), 20-38. doi: 10.11648/j.ijeedu.20251402.11
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Download@article{10.11648/j.ijeedu.20251402.11,
author = {Abdourahmane Ba and Mohamed Bille Barre},
title = {Determinants of Children's Preparedness for Primary Education in Djibouti: An Empirical Analysis Using IDELA Assessment
},
journal = {International Journal of Elementary Education},
volume = {14},
number = {2},
pages = {20-38},
doi = {10.11648/j.ijeedu.20251402.11},
url = {https://doi.org/10.11648/j.ijeedu.20251402.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijeedu.20251402.11},
abstract = {School readiness is a foundational predictor of long-term academic success and socio-economic mobility. In Djibouti, disparities in early learning outcomes reflect unequal preschool access, household-level differences, and regional disparities in service provision. This research addresses three questions: (1) What are the levels of school readiness across key developmental domains? (2) Which child-, household-, and region-level factors influence school readiness outcomes? (3) How do these outcomes vary across socio-economic and geographic groups? Drawing on data from 1,155 children aged 5-6 assessed through the International Development and Early Learning Assessment (IDELA), this research employs a multilevel mixed-effects model to estimate the effects of preschool attendance, caregiver engagement, and institutional context across four domains: literacy, numeracy, socio-emotional development, and physical development. The conceptual framework integrates Ecological Systems Theory, Human Capital Theory, and the Cumulative Risk Model to examine the interplay between home, school, and structural environments. Preschool attendance is the strongest predictor of literacy outcomes, associated with a 9.05-point gain (p < 0.001). Father’s participation in home literacy adds 2.64 points (p = 0.015), while the presence of a preschool-enrolled sibling contributes 3.92 points (p = 0.018). No statistically significant gender-based differences were found (p = 0.381). Parental education and behavioral engagement show strong positive associations with literacy and numeracy performance. Public school students score lower in numeracy than peers in private institutions (p < 0.05). Regional disparities are substantial. Preschool attendees in Djibouti-Ville score an average of 99.7, compared to 72.9 in Dikhil and 75.6 in Obock. Children in Tadjourah score 6.90 points lower than those in Ali-Sabieh (p = 0.026). Findings highlight the need for integrated policy reforms that expand equitable access, improve instructional quality, and strengthen parental engagement. Data-driven, multisectoral strategies will enhance school readiness and support Djibouti’s broader development goals.
},
year = {2025}
}
TY - JOUR T1 - Determinants of Children's Preparedness for Primary Education in Djibouti: An Empirical Analysis Using IDELA Assessment AU - Abdourahmane Ba AU - Mohamed Bille Barre Y1 - 2025/05/09 PY - 2025 N1 - https://doi.org/10.11648/j.ijeedu.20251402.11 DO - 10.11648/j.ijeedu.20251402.11 T2 - International Journal of Elementary Education JF - International Journal of Elementary Education JO - International Journal of Elementary Education SP - 20 EP - 38 PB - Science Publishing Group SN - 2328-7640 UR - https://doi.org/10.11648/j.ijeedu.20251402.11 AB - School readiness is a foundational predictor of long-term academic success and socio-economic mobility. In Djibouti, disparities in early learning outcomes reflect unequal preschool access, household-level differences, and regional disparities in service provision. This research addresses three questions: (1) What are the levels of school readiness across key developmental domains? (2) Which child-, household-, and region-level factors influence school readiness outcomes? (3) How do these outcomes vary across socio-economic and geographic groups? Drawing on data from 1,155 children aged 5-6 assessed through the International Development and Early Learning Assessment (IDELA), this research employs a multilevel mixed-effects model to estimate the effects of preschool attendance, caregiver engagement, and institutional context across four domains: literacy, numeracy, socio-emotional development, and physical development. The conceptual framework integrates Ecological Systems Theory, Human Capital Theory, and the Cumulative Risk Model to examine the interplay between home, school, and structural environments. Preschool attendance is the strongest predictor of literacy outcomes, associated with a 9.05-point gain (p < 0.001). Father’s participation in home literacy adds 2.64 points (p = 0.015), while the presence of a preschool-enrolled sibling contributes 3.92 points (p = 0.018). No statistically significant gender-based differences were found (p = 0.381). Parental education and behavioral engagement show strong positive associations with literacy and numeracy performance. Public school students score lower in numeracy than peers in private institutions (p < 0.05). Regional disparities are substantial. Preschool attendees in Djibouti-Ville score an average of 99.7, compared to 72.9 in Dikhil and 75.6 in Obock. Children in Tadjourah score 6.90 points lower than those in Ali-Sabieh (p = 0.026). Findings highlight the need for integrated policy reforms that expand equitable access, improve instructional quality, and strengthen parental engagement. Data-driven, multisectoral strategies will enhance school readiness and support Djibouti’s broader development goals. VL - 14 IS - 2 ER -
Geneve 3, Business Science Institute/IAE Lyon, Dakar, Senegal
National Education and Vocational Training, Djibouti Ville, Djibouti
