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Multinomial Logistic Regression Analysis of the Determinants of Students’ Academic Performance in Mathematics at Basic Education Certificate Examination

Received: 1 November 2016     Accepted: 14 December 2016     Published: 16 January 2017
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Abstract

The focus of the study is to use multinomial logistic regression model to analyze the determinants of students’ academic performance in mathematics. A simple random sample of 393 students was selected from a cohort of first year students of Zamse Senior High/Technical in the Bolgatanga Municipality. The students were admitted in the 2015/2016 academic year to pursue various programmes in the school. A questionnaire was used to gather data from the students. The results indicate that the occurrence of good performance in mathematics is largely dependent on sex of students with male students showing significantly good performance than female students. Another significant predictor of good academic performance in mathematics was the age of students; with younger students exhibiting good academic performance than older students. Mother’s employment also contributes significantly to good performance in mathematics with students whose mothers are employed showing good academic performance than their counterparts whose mothers are not employed.

Published in Higher Education Research (Volume 2, Issue 1)
DOI 10.11648/j.her.20170201.15
Page(s) 22-26
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), 2017. Published by Science Publishing Group

Keywords

Basic Education Certificate Examination, Multinomial Logit Model, Academic Performance and Regression

References
[1] Abiodun, O. O. & Issaiah, F. A. (2015). Academic Performance, Relationship with Gender and mode of Admission. Journal of Research & Method in Education, 5 (6): 59-66.
[2] Agresti, A. (2007). An Introduction to Categorical Data Analysis (2nd ed.). New Jersey: John Wiley & Sons, Inc.
[3] Aldrich, J. H. & Nelson, F. D. (1984). Linear probability, logit and probit models. Newbury Park, CA: Sade publications.
[4] Hosmer, D. W.& Lemeshow, S. (2000). Applied Logistic Regression (2nd ed.). New York: Wiley.
[5] Islam, M. M. (2014). Factors Influencing the Academic performance of Undergraduate Students in Sultan Qaboos University in Oman. Journal of Emerging Trends in Educational Research and Policy Studies, 5 (4): 396-404.
[6] Long, J. S. (1997). Regression Models for categorical and limited dependent variables. Thousand Oaks, CA: Sage.
[7] Nantomah, K. K. & Asampana, G. (2015). Teachers’ perception of the causes of students’ poor performance in mathematics at the Basic Education Certificate Examination. Researchjournali’s Journal of Education, 3 (9): 1-14.
[8] Park, K. H. & Kerr, P. M.(1990). Determinants of Academic Performance: A Multinomial Logit Approach. The Journal of Economic Education, 21 (2): 101-111.
[9] Petrucci, C. J. (2009). A Primer for Social Worker Researchers on How to Conduct a Multinomial Logistic Regression. Journal of Social Service Research, 35 (2): 193-205.
[10] Tachie, S. A., & Chireshe, R (2013) High Failure Rate in Mathematics Examinations in Rural Senior Secondary Schools in Mthatha District, Eastern Cape: Learners’ Attributions. Stud Tribes Tribals, 11 (1): 67-73.
[11] Tomar, D. & Agarwal, S.(2013). A survey on Data Mining approaches for Healthcare. International Journal of Bio-Science and Bio-Technology,.5 (2013), pp. 241-266.
[12] Tshabalala, T., & Ncube, A. C. (2013). Causes Of Poor Performance Of Ordinary Level Pupils In Mathematics In Rural Secondary Schools In Nkayi District: Learner’s Attributions. Nova Journal of Medical and Biological Sciences, 1 (1): 4-14.
[13] Sharker, S. & Rahman, M. D. M. (2015). Determinants of Academic Performance-Multinomial Logistic Regression Approach. International Journal of Scientific & Engineering Research, 6 (11): 1212-1216.
Cite This Article
  • APA Style

    Gaspar Asampana, Korah Kassim Nantomah, Evans Ayagikwaga Tungosiamu. (2017). Multinomial Logistic Regression Analysis of the Determinants of Students’ Academic Performance in Mathematics at Basic Education Certificate Examination. Higher Education Research, 2(1), 22-26. https://doi.org/10.11648/j.her.20170201.15

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    ACS Style

    Gaspar Asampana; Korah Kassim Nantomah; Evans Ayagikwaga Tungosiamu. Multinomial Logistic Regression Analysis of the Determinants of Students’ Academic Performance in Mathematics at Basic Education Certificate Examination. High. Educ. Res. 2017, 2(1), 22-26. doi: 10.11648/j.her.20170201.15

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    AMA Style

    Gaspar Asampana, Korah Kassim Nantomah, Evans Ayagikwaga Tungosiamu. Multinomial Logistic Regression Analysis of the Determinants of Students’ Academic Performance in Mathematics at Basic Education Certificate Examination. High Educ Res. 2017;2(1):22-26. doi: 10.11648/j.her.20170201.15

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  • @article{10.11648/j.her.20170201.15,
      author = {Gaspar Asampana and Korah Kassim Nantomah and Evans Ayagikwaga Tungosiamu},
      title = {Multinomial Logistic Regression Analysis of the Determinants of Students’ Academic Performance in Mathematics at Basic Education Certificate Examination},
      journal = {Higher Education Research},
      volume = {2},
      number = {1},
      pages = {22-26},
      doi = {10.11648/j.her.20170201.15},
      url = {https://doi.org/10.11648/j.her.20170201.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.her.20170201.15},
      abstract = {The focus of the study is to use multinomial logistic regression model to analyze the determinants of students’ academic performance in mathematics. A simple random sample of 393 students was selected from a cohort of first year students of Zamse Senior High/Technical in the Bolgatanga Municipality. The students were admitted in the 2015/2016 academic year to pursue various programmes in the school. A questionnaire was used to gather data from the students. The results indicate that the occurrence of good performance in mathematics is largely dependent on sex of students with male students showing significantly good performance than female students. Another significant predictor of good academic performance in mathematics was the age of students; with younger students exhibiting good academic performance than older students. Mother’s employment also contributes significantly to good performance in mathematics with students whose mothers are employed showing good academic performance than their counterparts whose mothers are not employed.},
     year = {2017}
    }
    

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    AB  - The focus of the study is to use multinomial logistic regression model to analyze the determinants of students’ academic performance in mathematics. A simple random sample of 393 students was selected from a cohort of first year students of Zamse Senior High/Technical in the Bolgatanga Municipality. The students were admitted in the 2015/2016 academic year to pursue various programmes in the school. A questionnaire was used to gather data from the students. The results indicate that the occurrence of good performance in mathematics is largely dependent on sex of students with male students showing significantly good performance than female students. Another significant predictor of good academic performance in mathematics was the age of students; with younger students exhibiting good academic performance than older students. Mother’s employment also contributes significantly to good performance in mathematics with students whose mothers are employed showing good academic performance than their counterparts whose mothers are not employed.
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Author Information
  • Department of Statistics, Bolgatanga Polytechnic, Bolgatanga, Ghana

  • Department of Statistics, Bolgatanga Polytechnic, Bolgatanga, Ghana

  • Zamse Senior High/Technical, Bolgatanga, Ghana

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