IDELA paper

Abstract

School readiness is highly salient in South Africa (SA), a country with extreme and persistent inequities that undermine early childhood development. The aim of this short-term longitudinal study was to identify social ecological factors influencing school readiness in young children from low-income settings in Cape Town, SA. Participants were 152 3-5-year-old children and their primary adult caregiver from low-income settings. Hierarchical linear regressions found that, compared to home- and community-level factors, child-level factors were the strongest predictors of scores on the International Development and Early Learning Assessment (IDELA, total and subscale scores for literacy, numeracy, social emotional and motor). At the child level, attending ECCE services was the strongest predictor, followed by early numeracy and age. Household socioeconomic status only predicted social emotional scores, and dysfunction in the parent-child relationship predicted literacy and total scores. These findings contribute to a contextually relevant understanding of school readiness in low-income SA settings.

Examining the Implementation of Artificial Intelligence in Early Childhood Education Settings in Ghana: Educators’ Attitudes and Perceptions towards Its Long-Term Viability

“…Data privacy and security are another significant concern for educators. AI systems in ECE settings collect and analyse vast amounts of data, including sensitive information about children and their learning progress (Draper et al, 2023). Educators worry about this data's potential misuse or mishandling, particularly in cases where third-party companies manage AI systems.…”