Exploring Particular Learner Factors Associated with South African Mathematics Learners’ Achievement: Gender Gap or Not

Mathematics is a gateway to science-related careers and all stakeholders want to improve the achievement levels in mathematics. In this study we use data from the Trends in International Mathematics and Science Study 2015 to investigate the association between the learner situational factors of gender, grade level age appropriateness, school location and test language familiarity with the mathematics achievement. We are particularly interested in whether gender can predict mathematics achievement, after taking into account these learner situational factors. The study used multiple regression to investigate the association between the variables where the mathematics achievement scores were calculated out of a possible 1000 scale points, with a mean of 500. The average score for the South African participants was 372. The regression predicts that learners who attend school in a rural and small village school are expected to achieve 63 and 48 points lower, respectively, than their counterparts from a similar background. In terms of the age effect, the regression predicts overall that a learner who is above the expected age for Grade 9 will get 60 points lower than a learner who is at the appropriate age the grade from a similar background. Furthermore the results show that if school location, familiarity with the test and age appropriateness are held constant, boys do better on average than girls by seven points and this is a significant effect. This result is unexpected since in the original data, the mean of the girls’ scores was on average higher than that of the boys. The study illustrates that gendered differences can only be adequately understood when other situational factors are considered. In order to improve the equity of the outcomes, targeted systemic interventions are necessary, which focus on improving the effectiveness of instruction and quality of learning opportunities so as to mediate the effect of these situational factors.

[1]  A. Donofrio.  Grade Repetition , 1977, PISA 2018 Results (Volume V).

[2]  Takashi Minemoto,et al.  Description of degradation of output performance for photovoltaic modules by multiple regression analysis based on environmental factors , 2019, Optik.

[3]  T. Zuze,et al.  Gender Inequalities in South African Schools: New Complexities , 2019, South African Schooling: The Enigma of Inequality.

[4]  M. Wissing,et al.  Representations of Hope, Goals, and Meaning From Lay Person’s Perspectives in Two African Contexts , 2018, Journal of Humanistic Psychology.

[5]  J. Harvey,et al.  The impact of language factors on learner achievement in Science , 2018 .

[6]  Natthapoj Vincent Trakulphadetkrai.  Where are the girls and women in mathematical picture books , 2017 .

[7]  D. Shepherd.  Gender, Self-concept and Mathematics and Science Performance of South African Grade 9 Students , 2017 .

[8]  N. Spaull,et al.  The ‘Martha Effect’: The compounding female advantage in South African higher education , 2017 .

[9]  H. Nel,et al.  Attraction, education and retention of technical women in South Africa , 2016, 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM).

[10]  M. Reiss,et al.  Girls in the UK have similar reasons to boys for intending to study mathematics post-16 thanks to the support and encouragement they receive , 2016 .

[11]  V. Reddy,et al.  TIMSS 2015: highlights of mathematics and science achievement of grade 9 South African learners , 2016 .

[12]  S. Bansilal,et al.  Examining success rates of teacher students : an activity theory analysis , 2015 .

[13]  P. Engelbrecht,et al.  Enacting understanding of inclusion in complex contexts: classroom practices of South African teachers , 2015 .

[14]  R. Mestry,et al.  The implications of the National Norms and Standards for school funding policy on equity in South African public schools , 2014 .

[15]  D. D. Plessis.  A Critical Reflection on Urban Spatial Planning Practices and Outcomes in Post-Apartheid South Africa , 2014 .

[16]  David C. Geary,et al.  Sex Differences in Mathematics and Reading Achievement Are Inversely Related: Within- and Across-Nation Assessment of 10 Years of PISA Data , 2013, PloS one.

[17]  Sarah Bansilal,et al.  Learning from previous experiments: readability in national mathematics assessments , 2013 .

[18]  Deevia Bhana,et al.  How women in higher education negotiate work and home: a study of selected women at a university in South Africa , 2012 .

[19]  D. Lam,et al.  Schooling as a Lottery: Racial Differences in School Advancement in Urban South Africa. , 2011, Journal of development economics.

[20]  Sean F. Reardon.  The widening academic achievement gap between the rich and the poor , 2011 .

[21]  M. Linn,et al.  New trends in gender and mathematics performance: a meta-analysis. , 2010, Psychological bulletin.

[22]  T. Mabogoane,et al.  Seeds of Their Struggle: The Features of Under- and Overage Enrolment among Grade 4 Learners in South Africa. CREATE Pathways to Access. Research Monograph No. 47. , 2010 .

[23]  Janet Shibley Hyde,et al.  Cross-national patterns of gender differences in mathematics: a meta-analysis. , 2010, Psychological bulletin.

[24]  Has gender equality in reading and mathematics achievement improved? , 2010 .

[25]  Y. Sayed,et al.  Physical access to schooling in South Africa: mapping dropout, repetition and age‐grade progression in two districts , 2009 .

[26]  B. Fleisch,et al.  Gender repetition: school access, transitions and equity in the ‘Birth‐to‐Twenty’ cohort panel study in urban South Africa , 2009 .

[27]  S. Howie.  System-Level Evaluation: Language and Other Background Factors Affecting Mathematics Achievement , 2005 .

[28]  J. Abedi,et al.  The Language Factor in Mathematics Tests , 2001 .