Individual Educational Achievement of Children Under Five Years Old as a Predictor of School Readiness

(Samia Mokhtar Mohamed Shahpo and Maymoonah Salah Hakim)

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Abstract

The current paper aims to review the body of literature on the topic of academic achievement prediction to establish if it is possible to predict the academic achievement of children before the end of their fifth year. A narrative synthesis performed on the body of the research obtained from Google Scholar, the ‘Jstor’ digital library and the university library, suggests that predictions can indeed be made regarding the academic achievement of this age group. The literature seems to suggest that both academic factors, such as Cumulative average, and non-academic factors, such as socioeconomic status, pre-school development and parental capital, can serve as moderately reliable predictors of academic performance from as early as 22 months. However, the evidence must be considered with caution as the definition and operationalisation of academic achievement varied across the research. In addition, factors such as motivation and self-efficacy were rarely taken into account. Still, the prediction of academic achievement in young children is possible. It can be improved with time as research continues to flourish in this area, and the issues regarding definition and measurement are recognised in the academic community

KEYWORDS
Early evaluation, expectation of achievement, educational performance, study readiness

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References

Allen, J.D. (2005). Grades as valid measures of academic achievement of classroom learning. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 78(5), 218–23. doi:10.3200/tchs.78.5.218-223 
Alexander, K.L., Entwisle, D.R., and Kabbani, N.S. (2001). The dropout process in life course perspective: Early risk factors at home and school. Teachers College Record, 103(5), 760–822.
Amrai, K., Motlagh, S.E., Zalani, H.A. and Parhon, H. (2011). The relationship between academic motivation and academic achievement students. Procedia-Social and Behavioral Sciences, n/a(15), 399–402.
Bergold, S. and Steinmayr, R. (2018). Personality and intelligence interact in the prediction of academic achievement. Journal of Intelligence, 6(2), 27.
Boyer, E.L. (1992). Ready to learn: A seven-step strategy. Principal, 71(5), 13–15.
Caro, D.H., (2009). Socio-economic status and academic achievement trajectories from childhood to adolescence. Canadian Journal of Education, 32(3), 558–90.
Chiekem, E. (2015). Grading practice as valid measures of academic achievement of secondary schools students for national development. Journal of Education and Practice, 6(26), 24–28.
Condron, J. (2007). Stratification and educational sorting: Explaining ascriptive inequalities in early childhood reading group placement. Social Problems, 54(1), 139–60.
Cronin, P., Ryan, F. and Coughlan, M. (2008). Undertaking a literature review: a step-by-step approach. British journal of nursing, 17(1), 38–43.
Davies, S. and Guppy, N. (2006). The Schooled Society: An Introduction to the Sociology of Education. Don Mills, ON: Oxford University Press.
Fan, X. and Chen, M. (2001). Parental involvement and students' academic achievement: A meta-analysis. Educational psychology review, 13(1), 1–22.
Feinstein, L. (2003). Very Early. Centre Piece: Summer.
Fong, C.J., Davis, C.W., Kim, Y., Kim, Y.W., Marriott, L. and Kim, S. (2017). Psychosocial factors and community college student success: A meta-analytic investigation. Review of Educational Research, 87(2), 388–424.
Goldthorpe, J.H. (1996). Class analysis and the reorientation of class theory: The case of persisting differentials in educational attainment. The British Journal of Sociology, 47(3), 481–505
Hanushek, E.A., P.E. Peterson, L.M. Talpey, and L. Woessmann. (2019). The achievement gap fails to close: half century of testing shows persistent divide between haves and have-nots. Education Next, 19 (3), 8.
Haveman, R. and Wolfe, B. (1994). The determinates of children's attainments: A review of methods and findings. Journal of Economic Literature, n/a(33), 1829–978.
Hellas, A., Ihantola, P., Petersen, A., Ajanovski, V.V., Gutica, M., Hynninen, T., Knutas, A., Leinonen, J., Messom, C. and Liao, S.N. (2018). Predicting academic performance: a systematic literature review. In: The 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education, Larnaca, Cyprus, 02–4/07/2018, 175–99. 
Hertzman, C. and Weins, M. (1996). Child development and long‐term outcomes: A population health perspective and summary of successful interventions. Social Science Medicine, 43(7), 1083–095.
Kim, J. and Suen, H.K., (2003). Predicting children’s academic achievement from early assessment scores: a validity generalization study, Early Childhood Research Quarterly, n/a(18), 547–66.  
Klapp, A. and Cliffordson, C. (2009). Effects of student characteristics on grades in compulsory school. Educational Research and Evaluation, n/a(15), 1–23
La Paro, K. and Pianta, R. (2000). Predicting children's competence in the early school years: A meta-analytic review. Review of Educational Research, 70(4), 443–84 
Leonard, M. (2005). Children, childhood, and social capital: Exploring the links. Sociology, n/a(39), 605−622
Mikolajewicz, N. and Komarova, S. (2019). Meta-analytic methodology for basic research: a practical guide. Frontiers in Physiology, n/a(10), 203.
Pishghadam, R. and Zabihi, R. (2011). Parental education and social and cultural capital in academic achievement. International Journal of English Linguistics, 1(2), 50.
Ray, M., Garavalia, L. and Murdock, T. (2003). Aptitude, motivation, and self-regulation as predictors of achievement among developmental college students. Research and Teaching in Developmental Education, 20(1), 5–21. 
Rabiner, D.L., Godwin, J. and Dodge, K.A. (2016). Predicting academic achievement and attainment: The contribution of early academic skills, attention difficulties, and social competence. School Psychology Review, 45(2), 250–67.
Robbins, S.B., Lauver, K., Le, H., Davis, D., Langley, R. and Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological bulletin, 130(2), 261.
Rumberger, R.W. (2004). Why students drop out of school. In: G. Or Field (Ed.), Dropouts In America: Confronting The Graduation Rate Crisis, pp. 131–155. Cambridge, MA: Harvard Education Press
Ryan, R. (2013). Cochrane Consumers and Communication Review Group: Data Synthesis and Analysis.  Available at: http://cccrg.cochrane.org, June 2013 (accessed on 26/11/2019).
Schlee, B. M., Mullis, A. K. and Shriner, M. (2009). Parents social and resource capital: Predictors of academic achievement during early childhood. Children and Youth Services Review, 31(2), 227–34.
Shetty, I.D., Shetty, D. and Roundhall, S. (2019). Student performance prediction. International Journal of Computer Applications Technology and Research, 8(5), 157–60.
Sirin, S. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research, 75(3), 417–53. 
Silva, C. and Fonseca, J. (2017). Educational Data Mining: A Literature Review. Berlin: Springer. 
Visvizi, A., Lytras, M.D. and Daniela, L. eds. (2018). The Future of Innovation and Technology in Education: Policies and Practices for Teaching and Learning Excellence. Bingley, UK: Emerald Publishing Limited.
Vulperhorst, J., Lutz, C., de Kleijn, R. and van Tartwijk, J. (2018). Disentangling the predictive validity of high school grades for academic success in university. Assessment and Evaluation in Higher Education, 43(3), 399–414.
York, T.T., Gibson, C. and Rankin, S. (2015). Defining and measuring academic success. Practical Assessment, Research, and Evaluation, 20(5), 1–20. DOI: 10.7275/hz5x-tx03