IDEAS home Printed from https://ideas.repec.org/a/rfa/ijcejl/v5y2022i1p16-28.html
   My bibliography  Save this article

Examining the Nature of Item Bias on Students’ Performance in National Examinations Council (NECO) Mathematics Senior School Certificate Dichotomously Scored Items in Nigeria

Author

Listed:
  • A. Alaba Adediwura
  • Asowo A. Patricia

Abstract

This study examined the nature of item bias on students’ performance in 2017 National Examinations Council (NECO) mathematics senior school certificate dichotomously scored items in Nigeria. The study adopted an ex-post-facto research design. A sample of 256,039 candidates was randomly selected from the population of 1,034,629 students who took the test. Instrument for data collection was 'Student Results' (SR). Data collected were analysed using the R language environment and an independent t-test. Results showed that the 2017 NECO Mathematics test was essentially unidimensional (-0.28 (<.20), ASSI = -0.31 (< 0.25) and RATIO = -0.31 (< 0.36). Results also showed that the nature of bias statistically encountered was a mean difference in scores bias, indicating that 86% (52 items), 79.1% (34 items), and 96% (56 items) were biased against male students, urban and public-school students, respectively. It was concluded that item bias is a notable factor that affected the validity of the NECO 2017 Mathematics test and conclusions drawn from the scores in Nigeria. Hence, it was recommended that before tests are administered for public use, examination bodies should make a careful review of tests through dimensionality assessment at the developmental stage to eliminate any perspectives that could cause test inequity among examinees.

Suggested Citation

  • A. Alaba Adediwura & Asowo A. Patricia, 2022. "Examining the Nature of Item Bias on Students’ Performance in National Examinations Council (NECO) Mathematics Senior School Certificate Dichotomously Scored Items in Nigeria," International Journal of Contemporary Education, Redfame publishing, vol. 5(1), pages 16-28, April.
    • Handle: RePEc:rfa:ijcejl:v:5:y:2022:i:1:p:16-28
    as

    Download full text from publisher

    File URL: https://redfame.com/journal/index.php/ijce/article/download/5402/5609
    Download Restriction: no
    File URL: https://redfame.com/journal/index.php/ijce/article/view/5402
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jinming Zhang, 2007. "Conditional Covariance Theory and Detect for Polytomous Items," Psychometrika, Springer;The Psychometric Society, vol. 72(1), pages 69-91, March.
    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. Merkle, Edgar C. & Steyvers, Mark & Mellers, Barbara & Tetlock, Philip E., 2017. "A neglected dimension of good forecasting judgment: The questions we choose also matter," International Journal of Forecasting, Elsevier, vol. 33(4), pages 817-832.
    2. César Merino-Soto & Arturo Juárez-García & Guillermo Salinas Escudero & Filiberto Toledano-Toledano, 2022. "Parametric and Nonparametric Analysis of the Internal Structure of the Psychosocial Work Processes Questionnaire (PROPSIT) as Applied to Workers," IJERPH, MDPI, vol. 19(13), pages 1-23, June.
    3. J. Straat & L. Ark & Klaas Sijtsma, 2013. "Comparing Optimization Algorithms for Item Selection in Mokken Scale Analysis," Journal of Classification, Springer;The Classification Society, vol. 30(1), pages 75-99, April.
    4. Jules Ellis, 2014. "An Inequality for Correlations in Unidimensional Monotone Latent Variable Models for Binary Variables," Psychometrika, Springer;The Psychometric Society, vol. 79(2), pages 303-316, April.
    5. Jules L. Ellis & Klaas Sijtsma, 2023. "A Test to Distinguish Monotone Homogeneity from Monotone Multifactor Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 387-412, June.
    6. Jinming Zhang, 2013. "A Procedure for Dimensionality Analyses of Response Data from Various Test Designs," Psychometrika, Springer;The Psychometric Society, vol. 78(1), pages 37-58, January.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:rfa:ijcejl:v:5:y:2022:i:1:p:16-28. 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: Redfame publishing (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.