The international literature demonstrates that school background matters when it comes to academic achievement in East Asia, the USA and Western Europe (Ho, 2003; Fuchs and Wobmann, 2004; Yang, 2003; see also Pascarella and Terenzini, 2005). Worldwide, students from higher SES families and those who studied in schools with higher average SES tend to achieve significantly better and exhibit higher self-efficacy than those from lower SES families as well as those who studied in schools with a lower mean SES (Ho, 2003).
Furthermore, Yang (2003) recognised an indirect relationship in OECD countries between achievement in mathematics and science, average family wealth, and average school mathematics and science scores for the school. The relationship between school SES and academic attainment is observed by Fuchs and Wobmann (2004) in their study of PISA which indicated that:
“…student characteristics (sex, whether they were born in the country where they attend school, whether they live with both parents, and whether either parent was born in the country), family background (number of books at home, parents’ educational level and degree of geographical isolation of home), instruction time, teachers’ sex, educational level and years of experience are all significantly related to mathematics, science and reading achievement”.
Pascarella and Terenzini (2005) also noted that the high school that one attended matters when it comes to academic achievement at university (see also Astin, 1993; Tinto, 1975).
Against this backdrop, some argue that at the college level it is quite clear that the child's own ability is even more important (Sewell & Shah, 1967; Haycock, 2001). Sewell and Shah
(1967), for instance, found that measured ability was nearly twice as important in Accounting when it comes to dropouts as was the social status of the family.
Many South African schools in rural areas still lack water, libraries, electricity, laboratories and computers (DoE, 2007). Participants in this study revealed that there were no science laboratories in some of their schools and that they had never seen a test tube before coming to university. These schools were unable to prepare students to pursue science subjects at university.
The quality of schooling aids or hinders students in their preparedness for further study or employment (Vermunt, 2005; see also TIMMS, 2003). Higher education participation in South Africa is generally low compared to international standards. The lack of participation of students from low SES households and families (Letseka, et al., 2008; CHE, 2007) is an international phenomenon. There is a plethora of explanations for this, including aptitude- based and biological factors. The lower ability of low SES children is partially explained by genetic predispositions which are not as significant as the environment (poverty and its embedded dictates such as nutrition or diet) (Gorard and See, 2008; Goldsmith, 1980;
Kleinman et al., 2002).
2.4.2 Size of Household and University Attendance
The literature has preoccupied itself with ‘quality versus quantity’ issues in families where a certain proportion of the wealth of the household has to be allocated to children for their well- being (Becker, 1973). The issue here is how the size of a household of family affects the allocation of resources based on the number of children vis-à-vis the resources available.
Becker’s quantity and quality model is a model of investment where households decide the level of resources allocated per child (Turkheimer et al., 2003). This study also indicated that respondents coming from smaller households were more likely to be the first generation to go to university. In poorer households, the number of young adults who attend tertiary education may be smaller than in richer households due to financial constraints (Branson, 2009; see also Margaret et al., 2001;Wolfe, 1982).
Two sets of extant studies, one focusing on scholastic achievement (Blake, 1981; Hauser, 1986) and the other on cognitive development (Wolfe, 1982), attest to the fact that children from bigger families experience lower academic performance than their counterparts from smaller families. Another body of literature shows that proportions of IQ variance attributable to genes and environment vary with SES in a non-linear manner (Turkheimer & Gottesman, 2003). Based on the preceding modelling it follows that “in impoverished families, 60% of the variance in IQ is accounted for by the shared environment, and the contribution of genes is close to zero; in wealthy households the result is almost exactly the opposite”(Gorard and See, 2008).
In low SES households, the decision on who accesses tertiary education and the allocation of scarce resources hinges on relative ability or aptitude amongst household members. Thus, the role of ability in deciding who goes to university is more significant in lower SES families.
(Branson et al., 2009).
The literature reveals that household size and composition have a significant impact on a child’s education. Children from larger families had slim odds of school attendance compared to those from smaller families (see Margaret et al., 2001). In 1996, 48% of South Africans lived in households with six or more family members (Margaret et al., 2001). The lower the level of education of the household head the larger the size of the household (Margaret et al., 2001). Individuals who come from families with more offspring are disadvantaged in the schooling process. Conversely, more recent studies suggest that the negative effects of
‘sibship’ size on children's educational achievement might be counterfeit (Conley, 2006).
Moreover, this study has revealed that many students coming from disadvantaged schools come from single parent homes where the household head is a female. Margaret et al. (2001) noted that that was true of 53% of those living in female-headed households and 45% of those living in male-headed households. Low income and poverty in single-parent homes lead to increased health problems and an inability to provide educational resources for their children.
Other studies also confirm the strong negative link between schooling and poverty, and that economic deprivation is a major hindrance to children’s education (see Mukudi, 2003 school level education in Kenya; Clarke, 2009 on higher education in the United Kingdom; see also Booth & Kee, 2005).
2.4.3 Material conditions at home
Ho’s (2010) study of family influences on science learning among Hong Kong adolescents identified three types of parental investment5 in their children’s education, namely: cultural (classical literature, poetry and works of art); educational (a desk to study at, textbooks and calculators); and material (a room of one’s own, a link to the Internet, a dishwasher, DVD or VCR player, a digital camera or video recorder, a musical instrument – piano, violin, and a pay TV channel). These resources were measured by the Programme for International Test and Assessment (PISA) questionnaire in 2006 in Hong Kong. Ho (2010) observed that students attained significantly higher grades in scientific literacy when they had access to these resources. Similarly, students with higher SES parents (Rothman, 2003), living in homes with modern possessions (Yang, 2003) and more books outperformed others (Mwetundila, 2001). Gorard (2008) observed that results of international tests like Trends in Mathematics and Science Study (TIMSS) affirmed that home background is a determinant of achievement in science across most countries.
In South Africa, studies have shown that poor schools especially in rural areas, lack resources such as sufficient classrooms, have poor access to services such as water and electricity, no landline telephones and hence no Internet access, and that there are few public or school libraries (see Nelson Mandela Foundation, 2005; Gardiner, 2007); they also suffer from a shortage of textbooks and relevant learning and teaching material (Mohlala, 2010).
Individuals who attend disadvantaged schools in South Africa are usually from disadvantaged socio-economic backgrounds (Munro et al., 2011) with a very low Household Expenditure levels (see Margaret etal., 2001).
Ho’s (2010) study on parental investment at home can be applied to both school level and higher education institutions. At the higher education level, students (particularly those from disadvantaged backgrounds) rely on higher education institutions or government funding facilities such as NSFAS for educational, cultural and material resources, hence the importance of material conditions at home in relation to academic progress.
5 Parental investment is defined by Ho (2010) as the economic and cultural resources provided by parents for their children’s education.
2.4.4 Food [In]Security and Academic Progress
Most of the literature that attempts to explicate the relationship between food or nutrition and education has focused on elementary levels of basic education. Furthermore, while there have been few sociological studies on the link between nutrition and educational outcomes, some studies have shown that the nutritional environment in the home is linked to household socio- economic status. In turn, household socio-economic status is a predictor of children’s academic performance, and a significant mediator of poverty effects on schooling for children in early primary grades (Pollit, 1990, international trends; Kgosana, 2012 South African situation at university level in general). Insecure access to nutritious food is a common existential reality for poor households in developing countries (see Hannum and Yu (2007). In the South African context, a Ministerial report on the provision of student housing has observed that hunger and poor nutrition impacted on attendance, concentration levels during lectures and academic progress which in turn leads to attrition (Nzimande, 2012).
In a study of Kenyan middle-school children, Mukudi (2003) observed that the high incidence of nutritional stress was a significant educational problem in this population; and that the association between attendance rate and nutrition status was a function of socio- economic status. The predictive effect of nutrition status on educational achievement is more evident for girls with poor socio-economic status (Mukudi, 2003). Preventive supplementation studies suggest a causal relationship between poor diet and problems at school (Pollitt et al., 1993). Pollitt (1990) observed that nutritional deficiencies and poor health in primary school children were among the factors contributing to poor school enrolment, absenteeism, early dropout and poor classroom performance. A number of other studies have revealed that poor nutrition and diet affect academic performance negatively (American School Food Service Association, 1989), while proper nutrition relieves hunger and enhances academic performance and children’s ability to succeed (Murphy et al., 1998;
Kleinman et al., 1998). While attention has been given to the association between most SES variables and the academic performance of children, not much has been said or done about the effects of nutrition on academic performance in general, let alone in higher education (see Pollit, 1990, italics mine). This is a challenge to policy makers and the government.
An unpublished study by Munro et al. (2011)at UKZN, found that on average students spend R127.93 on food per week and are significantly more likely to go hungry at the end of a semester near examination time. Students who relied on financial aid were found to be more susceptible to food insecurity than those who did not. They found that:
“...around one in ten students (11%) are highly vulnerable to food insecurity, with about one in three students (38.3%) reporting some level of vulnerability to food insecurity”.