Empirical estimates of education production are very few in the case of Tunisia due to non availability of data. Fortunately, trends in international mathematics and science study starts to fill this gap by providing data on students’ achievement. TIMSS 2011 revealed that the average performance of Tunisia student is at the lower end of the distribution of the average score of all participating countries Tunis took the 47th in mathematics over 50 countries. Despite the abundant resources and reforms undertaken by the educational community Tunisia student suffer from a very low primary quality of education as measured by mathematics test score. This article attempts to find out the impact of the home environment, school resources and teacher quality on the students’ educational achievement at fourth grade in mathematics., we estimate educational production functions using OLS and then repeat the exercise estimating quantile regressions at different part of the score distribution in order to analyze if there are differences in the variables affecting test scores along the scores distribution and not just at the mean of the distribution. The results show that the home environment, school resources and teacher resource are key determinants of primary education performance. In order to to improve primary education performance, it is recommended that policymakers and educational authorities focus on strengthening all three key determinants: enhancing support for families to create a conducive learning environment at home, investing in better school resources and infrastructure, and providing ongoing professional development and support for teachers. By addressing these areas comprehensively, educational institutions can create a more effective and supportive framework that promotes better learning outcomes for all students.
Published in | International Journal of Elementary Education (Volume 13, Issue 3) |
DOI | 10.11648/j.ijeedu.20241303.11 |
Page(s) | 39-48 |
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), 2024. Published by Science Publishing Group |
TIMSS 2011, Primary Education, Quality, Mathematics Achievement, Family Background, School Resources, Ordinary Least Sequare, Quantile Regression, Tunisia
[1] | Altonji and Dunn (1996) The Effects of Family Characteristics on the Return to Education The Review of Economics and Statistics, Vol. 78, No. 4(Nov., 1996), pp. 692-704 (13 pages) |
[2] | Brunello and checchi (2005) “School quality and family background in Italy”. Economics of Education Review, 24(5), 563-577. |
[3] | Buchinsky. M Recent advances in quantile regression models: a practical guideline for empirical research. Journal of Human Resources, pages 88–126, 1998. |
[4] | Caldas, S. J., & Bankston, C. III. (1997). Effect of school population socioeconomic status on individual academic achievement. The Journal of Educational Research, 90(5), 269–277. |
[5] | Campbell, J. R., Donahue, P. L., Reese, C. M., & Phillips, G. W. (1996). NAEP reading report card for the nation and the states. Washington, DC: U.S. Department of Education. |
[6] | Card, D. and Krueger, A. B. (1996) School resources and student outcomes: an overview of the literature and new evidence from north and South Carolina. Journal of Economic Perspectives, 10, 31-50. |
[7] | Cassidy, T. and Lynn, R. (1991). Achievement motivation, educational attainment, cycles of disadvantage and social competence: Some longitudinal data. British J. Educ. Psychol. 61: 1-12. |
[8] | Chevalier, A., Lanot, G., (2002). “The Relative effect of family characteristics and financial situation on educational achievement” Education Economics, 10(2), 166-180. |
[9] | Chiu, M. M., (2007). “Families, economies, cultures, and science achievement in 41 countries: country, school, and student level analyses”, Journal of Family Psychology, 21(3), 510-519. |
[10] | Dahl, G. B., & Lochen, M. (2005). The Impact of Family Income on Educational Outcomes: Evidence from a Scandinavian Context. Economics of Education Review, 24(4), 347-359. |
[11] | De Broueker, P., Underwood, K. (1998). “Intergenerational education mobility: a international comparison with a focus on postsecondary education” Education Quearterly Review, 5(2), 30-45. |
[12] | Duplooy, J. J. (1988). Mother’s Education and Its Influence on Child Development. Journal of Child Development, 59(2), 310-327. |
[13] | Farooq, M.S; Chaudhry, A. H; Shafiq, M and Berhanu, G. (2011): Factors affecting students’ quality of academic performance: A case of secondary school level. Journal of quality and technology Management, 7(2), 01-14. |
[14] | Ferguson, R. F. & Ladd, H. F. (1996). How and why money matters: An analysis of Alabama schools. In H. F. Ladd (Ed.), Holding schools accountable: Performance-based reform in education. Washington, DC: The Brookings Institution. |
[15] | Fuller (1986). “Teachers, Pedagogy and Student Achievement: Colombia, Guatamala, Nicaragua, Peru, Uganda. New Schools (Escuela Nueva). |
[16] | Greenberg, J., & Teixeira, R. (1995). Urban and Rural Student Performance on the National Assessment of Educational Progress: A Comparative Analysis. Educational Policy Studies, 23(3), 147-162. |
[17] | Hanushek, E. A. (1996). School resources and student performance. In G. Burtless (Ed.), Does money matter? The effect of school resources on student achievement and adult success (pp. 43-73). Washington, DC: Brookings Institution. |
[18] | Hanushek, E. A. (1986). The economics of schooling: Production and efficiency in public schools. Journal of Economic Literature, 24(3), 1141–77. |
[19] | Hanushek, E.A. (1979). Conceptual and empirical issues in the estimation of educational production functions. Journal of human Resources, pages 351–388. |
[20] | Hanushek, E.A. (1997). Assessing the Effect of School Resources on Student Performance: An Update. Educational Evaluation and Policy Analysis 19(2): 141-164. |
[21] | Hedges, L. V., & Greenwald, R. (1996). Effects of School Resources on Student Achievement. Review of Educational Research, 66(3), 257-299. |
[22] | Hedges, I.V. Laine, R.D. and Greenwald, R. (1994). Does Money Mater? A Meta-Analysis of Studies of the Effects of Differential School Inputs on Student outcomes. Educational Researchers 23(3): 5-14. |
[23] | Heyneman, S. P., Layne-Farrar, A., & Todd, P. E. (1996a). The relationship between school quality and student achievement: The case of the developing world. International Journal of Educational Development, 16(1), 35-44. |
[24] | Jeynes, W. H. (2002). Examining the Effects of Parental Involvement on Student Achievement: A Meta-Analysis. Journal of Educational Research, 96(4), 270-280. |
[25] | Jubber, K. (1990). The home and family environment and its impact on school performance. South African Journal of Sociology, 21(1), 1-11. |
[26] | Kellaghan, T. (1977). Relationships between home-environment and scholastic behavior of a disadvantaged population. Journal of Educational Psychology, 69(6), 754-760. |
[27] | Koenker, R., and Bassett, G. Jr. (1978).” Regression quantiles. Econometrica: journal of the Econometric Society”, pages 33–50. |
[28] | Koenker, R and Hallock, K. (2001). “Quantile regression: An introduction”. Journal of Economic Perspectives, 15(4): 43–56. |
[29] | Krashen, S. (2005). The hard work hypothesis: Is doing your homework enough to overcome the effects of poverty? Multicultural Education, 12(4), 16-19. |
[30] | Lippman, L., Kaye, K., & McArthur, E. (1988). Child and Family Characteristics Associated with School Success. Educational Evaluation and Policy Analysis, 10(2), 175-186. |
[31] | Lopez, J. (1995). The Influence of Family Background on Academic Achievement: A Study of Urban and Rural Students. Journal of Educational Research, 88(3), 159-165. |
[32] | Lockheed M, E and Long ford N, T. (1991). School effects on mathematics achievement gain in Thailand. |
[33] | Ma, X., & Klinger, D. A. (2000). The Role of Parent Involvement in Student Achievement: A Review of the Literature. Educational Policy Analysis Archives, 8(1), 1-20. |
[34] | Marjoribanks, K. (1972). The Effects of Family Background on Educational Achievement. Journal of Educational Psychology, 63(3), 262-269. |
[35] | Mayer, S. (1997). What money can't buy? Cambridge, MA: Harvard University Press. |
[36] | Mitchell, D., & Collom, E. (2001). The Impact of School Resources on Student Achievement: A Longitudinal Analysis. Educational Evaluation and Policy Analysis, 23(3), 145-163 |
[37] | Mullis, I. V. S., Campbell, J. R., & Farstrup, A. E. (1994). The National Assessment of Educational Progress: A Summary of the 1994 Findings. Educational Testing Service. |
[38] | Muola, J. M. (2010). A Study of the relationship between academic achievement motivation and home environment among standard eight pupils. Educational Research and Reviews vol. 5(5), pp. 213-217. |
[39] | Murnane, R. J., and Phillips, B. R. (1981). What do effective teachers of inner-city children. |
[40] | Parelius, D., & Parelias, A. (1987). The Impact of Socioeconomic Factors on Educational Achievement: A Comparative Study. Educational Researcher, 16(4), 24-30. |
[41] | Spiegel, D. (1994). A portrait of parents of successful readers. ERIC Document Reproduction Service NO.ED353548. |
[42] | Tiebout, C. (1956). A pure theory of local expenditures. Journal of Political Economy, 64, 416-424. |
[43] | Waters, J.T. and Marzano, R.J. (2006). School District Leadership That Works: The Effect of Superintendent Leadership on Student Achievement. Mid-Continent Research for Education and Learning. |
[44] | White, K. 1982. The relation between Socioeconomic Status and Academic Achievement. Psychological Bulletin 91: 461-481. |
[45] | Willms, J. D. (2000). Standards of care: Investments to improve children’s educational. |
APA Style
Soudani, K. (2024). Determinants of the Quality of Primary Education in Tunisia: A Micro-Econometric Analysis Applied to the TIMSS 2011 Study. International Journal of Elementary Education, 13(3), 39-48. https://doi.org/10.11648/j.ijeedu.20241303.11
ACS Style
Soudani, K. Determinants of the Quality of Primary Education in Tunisia: A Micro-Econometric Analysis Applied to the TIMSS 2011 Study. Int. J. Elem. Educ. 2024, 13(3), 39-48. doi: 10.11648/j.ijeedu.20241303.11
AMA Style
Soudani K. Determinants of the Quality of Primary Education in Tunisia: A Micro-Econometric Analysis Applied to the TIMSS 2011 Study. Int J Elem Educ. 2024;13(3):39-48. doi: 10.11648/j.ijeedu.20241303.11
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TY - JOUR T1 - Determinants of the Quality of Primary Education in Tunisia: A Micro-Econometric Analysis Applied to the TIMSS 2011 Study AU - Kaouther Soudani Y1 - 2024/09/26 PY - 2024 N1 - https://doi.org/10.11648/j.ijeedu.20241303.11 DO - 10.11648/j.ijeedu.20241303.11 T2 - International Journal of Elementary Education JF - International Journal of Elementary Education JO - International Journal of Elementary Education SP - 39 EP - 48 PB - Science Publishing Group SN - 2328-7640 UR - https://doi.org/10.11648/j.ijeedu.20241303.11 AB - Empirical estimates of education production are very few in the case of Tunisia due to non availability of data. Fortunately, trends in international mathematics and science study starts to fill this gap by providing data on students’ achievement. TIMSS 2011 revealed that the average performance of Tunisia student is at the lower end of the distribution of the average score of all participating countries Tunis took the 47th in mathematics over 50 countries. Despite the abundant resources and reforms undertaken by the educational community Tunisia student suffer from a very low primary quality of education as measured by mathematics test score. This article attempts to find out the impact of the home environment, school resources and teacher quality on the students’ educational achievement at fourth grade in mathematics., we estimate educational production functions using OLS and then repeat the exercise estimating quantile regressions at different part of the score distribution in order to analyze if there are differences in the variables affecting test scores along the scores distribution and not just at the mean of the distribution. The results show that the home environment, school resources and teacher resource are key determinants of primary education performance. In order to to improve primary education performance, it is recommended that policymakers and educational authorities focus on strengthening all three key determinants: enhancing support for families to create a conducive learning environment at home, investing in better school resources and infrastructure, and providing ongoing professional development and support for teachers. By addressing these areas comprehensively, educational institutions can create a more effective and supportive framework that promotes better learning outcomes for all students. VL - 13 IS - 3 ER -