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The multilevel analysis of students’ achievement: Evidence from Morocco

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  • Abdellatif Chatri
  • Otman Chahbi
  • Mustapha Snihji

Abstract

This paper, using multi‐level modelling, sought to highlight student‐level and school‐level characteristics that differentiate the academic performance in mathematics from a sample of 6080 Moroccan secondary students who participated in the 2011 Trends in International Mathematics and Science Study (TIMSS) test. The results indicated little evidence to support the Heyneman–Loxley effect, as they showed that individual and family characteristics were the strongest determinants of achievement compared to the schools’ factors. Students scored higher when they were boys, were younger, were more self‐confident, were more ambitious, and felt secure in school. They also scored higher when they came from families with a higher socioeconomic status, particularly when their parents were able to ensure the availability of learning resources, and were of a higher level of education. Finally, schools were matter for their pupil achievement mainly through the location channel, as urban pupils outperformed rural ones. However, the other school characteristics, including those related to teachers, played a negative, or at best neutral, role in pupil outcomes. These findings have important public policy implications. Redesigning education policy towards improving the school's environment and fostering inclusivity would be needed to enhance learning performance of Moroccan students.

Suggested Citation

  • Abdellatif Chatri & Otman Chahbi & Mustapha Snihji, 2021. "The multilevel analysis of students’ achievement: Evidence from Morocco," African Development Review, African Development Bank, vol. 33(1), pages 117-129, March.
  • Handle: RePEc:bla:afrdev:v:33:y:2021:i:1:p:117-129
    DOI: 10.1111/1467-8268.12497
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    1. Eric Hanushek & Ludger Woessmann, 2012. "Do better schools lead to more growth? Cognitive skills, economic outcomes, and causation," Journal of Economic Growth, Springer, vol. 17(4), pages 267-321, December.
    2. Steven G. Rivkin & Eric A. Hanushek & John F. Kain, 2005. "Teachers, Schools, and Academic Achievement," Econometrica, Econometric Society, vol. 73(2), pages 417-458, March.
    3. Wo[ss]mann, Ludger & West, Martin, 2006. "Class-size effects in school systems around the world: Evidence from between-grade variation in TIMSS," European Economic Review, Elsevier, vol. 50(3), pages 695-736, April.
    4. Thomas Fuchs & Ludger Wößmann, 2008. "What accounts for international differences in student prformance? A re-examination using PISA data," Studies in Empirical Economics, in: Christian Dustmann & Bernd Fitzenberger & Stephen Machin (ed.), The Economics of Education and Training, pages 209-240, Springer.
    5. Nadir Altinok & Geeta Kingdon, 2012. "New Evidence on Class Size Effects: A Pupil Fixed Effects Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 203-234, 04.
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    Cited by:

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    2. Ilan Strauss & Gilad Isaacs & Josh Rosenberg, 2021. "The effect of shocks to GDP on employment in SADC member states during COVID‐19 using a Bayesian hierarchical model," African Development Review, African Development Bank, vol. 33(S1), pages 221-237, April.

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