# **1 Introduction**

Low- and middle-income countries (LMICs) have made enormous progress in expanding access to education and enrolling children in primary and, increasingly, secondary education. Learning, however, has lagged this growth in schooling (World Bank 2018a). The preparation of children to learn and challenges in early childhood development, including lack of access to quality preprimary education, further limit learning (Berlinski, Galiani, and Manacorda 2008; Berlinski, Galiani, and Gertler 2009; World Bank 2018a). Recent efforts to expand pre-primary education to enhance learning have underscored the importance of providing high-quality pre-primary education in order to generate developmental gains (Araujo et al. 2016; Bouguen et al. 2018; Blimpo et al. 2019; Wolf et al. 2019).

Quality assurance systems (QAS) have been identified as an important part of promoting quality learning. Two of the three key recommendations of the World Bank (2018a) flagship report on education were to assess learning and act on evidence – actions that can be enabled by a QAS. In line with this recommendation, many countries around the world are developing or strengthening their QAS (Raikes et al. 2020), including the design and implementation of short, feasible tools that can be used to collect data on school- and classroom-level quality indicators. QAS are important particularly for ensuring the quality of early learning, since at this stage of development, there are no national assessments of child development and learning to draw upon when considering policy actions (World Bank 2013; Raikes, Neuman, and Burton 2019). There is a substantial push in conjunction with expanding pre-primary to ensure it is high quality, which has led to a rising number of LMICs working to develop QAS (Raikes, Sayre, and Lima 2021). There has been some research providing advice on the design of QAS and especially standards and monitoring tools for LMICs, including details on case studies and countries’ practices (Raikes, Neuman, and Burton 2019; Raikes, Sayre, and Lima 2021).

Yet there has been very little (to the best of the authors’ knowledge, none to date) research actually using data from QAS to illustrate their potential – or pitfalls – in supporting quality learning for all in LMICs. Although there is information from high-income countries about their QAS, information from LMICs is limited (Anderson et al. 2017; Raikes, Neuman, and Burton 2019). This is partly a data problem; countries’ ministries or agencies responsible for the QAS may release the results of quality assurance efforts, such as school report cards or national reports, but not the microdata nor research validating the QAS itself. Even national reports or databases are relatively rare in LMICs. For instance, only 29% of countries, in a study of early childhood care and education QAS in 14 Sub-Saharan African countries, had their monitoring data reported back to a national database (Raikes, Sayre, and Lima 2021).

This paper investigates the potential ability of QAS to systematically monitor quality and inform action, drawing on data from pre-primary in the Arab Republic of Egypt. The effectiveness of QAS depends on the accuracy and relevance of the data collected through QAS tools used to monitor quality practices within classrooms. Our research questions are:

- (1) How consistently do the tools used within a QAS measure quality?

- (2) What are potential sources or reasons for any inconsistency?

- (3) In light of the degree of measurement error found in measuring quality, how should data from QAS be used to undertake quality enhancement?

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