Socio-economic status (SES) is an important construct when examining differences in outcomes, be they in education, health, psychology, the labour market or society more generally. SES can be considered both an input-control... [ view full abstract ]
Socio-economic status (SES) is an important construct when examining differences in outcomes, be they in education, health, psychology, the labour market or society more generally. SES can be considered both an input-control construct to monitor equity in outcomes, and a substantive construct that relates to outcomes through other constructs. These relationships have been found to apply in high- as well as low- and middle-income countries (LMICs) and reducing SES-related access and achievement gaps is an important step in ensuring inclusive and quality education for all and promoting lifelong learning.
This paper illustrates that there is some conflicting evidence regarding the magnitude of the relationship between SES and outcomes. This, however, may be partly due to the inappropriateness of widely-used measures of SES in assessment programs in LMICs. This paper reports the results of a critical review of international assessments and new empirical analysis. International perspectives are drawn from Australian, Afghanistan, India, Pacific Islands (e.g., Solomon Islands), East and South Africa (e.g., Kenya, Zimbabwe, Uganda), as well as international and national assessments including included IEA PIRLS and TIMSS, IEA ICCS, OECD PISA and PIAAC, SACMEQ, CONFEMEN PASEC, UNESCO LLECE, Citizen-led assessments (ASER India, ASER Pakistan, Uwezo Kenya, Tanzania and Uganda, Beekunko Mali, Jàngandoo Senegal), ACER MTEG Afghanistan, and Indonesia QEM.
The empirical analysis shows that measures of wealth in international assessments may not behave appropriately across all contexts and proposes a new method of deriving a scale of household wealth and also uses the results of the critical review to propose future approaches to selecting background questionnaire items appropriate for countries from different income and inequality contexts. The key implication is that careful analysis can be used to support countries to better measure social and demographic phenomena in order to better understand equity in learning outcomes.
