IDEAS home Printed from https://ideas.repec.org/a/rnd/arjevr/v8y2018i4p28-42.html
   My bibliography  Save this article

The Effect of Mathematics and Physical Science on Matriculants’ Overall Performances: Analysis Using Multilevel Model

Author

Listed:
  • M. E Letsoalo

Abstract

This comparative, cross-sectional, quantitative and ex-post-facto designed study used secondary and correlated data to compare the likelihood of passing matric between learners from Gauteng and Western Cape provinces, even after adjusting for subject-type. This study attempted to assess the relation between school resources input, subject offered, learner’s gender and learners’ academic achievements. The data used in this study were supplied by the Umalusi Council. The dataset contained 145783 matric learners (65245 [44.75%] males and 80538 [55.25%] females) who wrote the matric examinations in Gauteng and Western Cape provinces in November 2009. The unadjusted model indicated that learners in Western Cape were significantly 1.193 more likely to pass matric than learners in Gauteng province (p < 0.001, OR = 1.193, 95%CI: 1.164 - 1.223). The adjusted model results indicated that learners in the Western Cape province were 1.5122 more likely to pass matric when compared to learners in Gauteng province (p < 0.001, OR = 1.512, 95%CI: 1.471 - 1.555). These results indicate that the odds of passing matric, after adjusting for science subjects, increased in favour of learners in the Western Cape Province. It can be concluded that the Western Cape Province provides more enabling conditions to ensure matriculants’ superior performance. It is suggested the strategies to improve the quality of mathematics and science educators need to be implemented, especially in Gauteng province. Also, the policy that advocates for the differentiation approach should be adopted, as opposed to the current policy that advocates for a more general, rigid approach that does not recognise the inherent differences in the provinces.

Suggested Citation

  • M. E Letsoalo, 2018. "The Effect of Mathematics and Physical Science on Matriculants’ Overall Performances: Analysis Using Multilevel Model," Journal of Education and Vocational Research, AMH International, vol. 8(4), pages 28-42.
  • Handle: RePEc:rnd:arjevr:v:8:y:2018:i:4:p:28-42
    DOI: 10.22610/jevr.v8i4.2158
    as

    Download full text from publisher

    File URL: https://ojs.amhinternational.com/index.php/jevr/article/view/2158/1606
    Download Restriction: no

    File URL: https://ojs.amhinternational.com/index.php/jevr/article/view/2158
    Download Restriction: no

    File URL: https://libkey.io/10.22610/jevr.v8i4.2158?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kwabena A Kyei & T Maboko, 2016. "Performance of High School Students in Vhembe District," Journal of Economics and Behavioral Studies, AMH International, vol. 8(1), pages 50-57.
    2. Chowa, Gina A.N. & Masa, Rainier D. & Ramos, Yalitza & Ansong, David, 2015. "How do student and school characteristics influence youth academic achievement in Ghana? A hierarchical linear modeling of Ghana YouthSave baseline data," International Journal of Educational Development, Elsevier, vol. 45(C), pages 129-140.
    3. Gijsbert Stoet & David C Geary, 2013. "Sex Differences in Mathematics and Reading Achievement Are Inversely Related: Within- and Across-Nation Assessment of 10 Years of PISA Data," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-10, March.
    4. Tansel, Aysit, 2002. "Determinants of school attainment of boys and girls in Turkey: individual, household and community factors," Economics of Education Review, Elsevier, vol. 21(5), pages 455-470, October.
    5. Hakkinen, Iida & Kirjavainen, Tanja & Uusitalo, Roope, 2003. "School resources and student achievement revisited: new evidence from panel data," Economics of Education Review, Elsevier, vol. 22(3), pages 329-335, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nguyen, Ha, 2015. "The evolution of the gender test score gap through seventh grade: New insights from Australia using quantile regression and decomposition," MPRA Paper 67586, University Library of Munich, Germany.
    2. Letsoalo M.E, 2017. "Disaggregated Analysis of Performances of Grade 12 Learners in Gauteng Province, Republic of South Africa," Journal of Education and Vocational Research, AMH International, vol. 8(2), pages 34-44.
    3. Huong Thu Le & Ha Trong Nguyen, 2018. "The evolution of the gender test score gap through seventh grade: new insights from Australia using unconditional quantile regression and decomposition," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 7(1), pages 1-42, December.
    4. Aysit Tansel & Nil Demet Gungor, 2003. "Brain Drain from Turkey: Survey Evidence of Student Non-Return," Working Papers 0307, Economic Research Forum, revised Mar 2003.
    5. Frempong, Raymond Boadi & Orkoh, Emmanuel & Kofinti, Raymond Elikplim, 2021. "Household's use of cooking gas and Children's learning outcomes in rural Ghana," Energy Economics, Elsevier, vol. 103(C).
    6. Okuneye Babatunde A & Obasan Kehinde A, 2014. "Determinants of Demand for Primary Education in Nigeria," International Journal of Economics and Empirical Research (IJEER), The Economics and Social Development Organization (TESDO), vol. 2(2), pages 44-51, February.
    7. Ferry Prasetyia, 2019. "The role of local government policy on secondary school enrolment decision in Indonesia," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 9(2), pages 139-172, June.
    8. Orazem, Peter F. & King, Elizabeth M., 2008. "Schooling in Developing Countries: The Roles of Supply, Demand and Government Policy," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 55, pages 3475-3559, Elsevier.
    9. Cin, Firdevs Melis & Walker, Melanie, 2016. "Reconsidering girls’ education in Turkey from a capabilities and feminist perspective," International Journal of Educational Development, Elsevier, vol. 49(C), pages 134-143.
    10. Borgna, Camilla & Struffolino, Emanuela, 2017. "Pushed or pulled? Girls and boys facing early school leaving risk in Italy," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 61, pages 298-313.
    11. Giofrè, D. & Allen, K. & Toffalini, E. & Mammarella, I.C. & Caviola, S., 2022. "Decoding gender differences: Intellectual profiles of children with specific learning disabilities," Intelligence, Elsevier, vol. 90(C).
    12. Gracia De Renteria, Pilar & Ferrer Perez, Hugo & Philippidis, George & Sanjuan Lopez, Ana Isabel, 2021. "Capturing the drivers of social SDGs: An econometric analysis of the dimensions of health and education," Conference papers 333271, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    13. Nadir Altinok & Abdurrahman Aydemir, 2015. "The Unfolding of Gender Gap in Education," Working Papers halshs-01204805, HAL.
    14. Shulamit Kahn & Donna Ginther, 2017. "Women and STEM," NBER Working Papers 23525, National Bureau of Economic Research, Inc.
    15. Mihails Hazans & Ija Trapeznikova, 2006. "Access to Secondary Education in Albania: Incentives, Obstacles, and Policy Spillovers," SSE Riga/BICEPS Research Papers 2006-1, Baltic International Centre for Economic Policy Studies (BICEPS);Stockholm School of Economics in Riga (SSE Riga).
    16. Caner, Asena & Okten, Cagla, 2010. "Risk and career choice: Evidence from Turkey," Economics of Education Review, Elsevier, vol. 29(6), pages 1060-1075, December.
    17. Trine Filges & Jens Dietrichson & Bjørn C. A. Viinholt & Nina T. Dalgaard, 2022. "Service learning for improving academic success in students in grade K to 12: A systematic review," Campbell Systematic Reviews, John Wiley & Sons, vol. 18(1), March.
    18. Maarten Jan Wensink & Linda Juel Ahrenfeldt & Sören Möller, 2020. "Variability Matters," IJERPH, MDPI, vol. 18(1), pages 1-8, December.
    19. Maitra, Pushkar & Mani, Subha, 2017. "Learning and earning: Evidence from a randomized evaluation in India," Labour Economics, Elsevier, vol. 45(C), pages 116-130.
    20. Gevrek, Z. Eylem & Seiberlich, Ruben R., 2014. "Semiparametric decomposition of the gender achievement gap: An application for Turkey," Labour Economics, Elsevier, vol. 31(C), pages 27-44.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rnd:arjevr:v:8:y:2018:i:4:p:28-42. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Muhammad Tayyab (email available below). General contact details of provider: https://ojs.amhinternational.com/index.php/jevr .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.