A detailed diagnostic research tool and a pilot of the new national QAS tool for Egyptian Kindergartens (KGs) were implemented on a nationally representative sample of schools with KGs, with overlapping data collection. Both government and data collection firm enumerators were used (and randomly assigned to districts). We compare these data sources to assess how consistent results are across the QAS tool and the diagnostic research tool, overall, and for particular items. We specifically measure exact agreement of items and Cohen’s kappa coefficient. We do not and cannot know whether the QAS tool or diagnostic research tool data, or neither, are ultimately “right or wrong,” but relatively consistent results from different measures are an important prerequisite to data quality and usability. Data were collected on the learning environment and child development outcomes. We examine what school, class, teacher, student, and enumerator characteristics predict greater consistency in logit models for each dimension of quality in Egypt’s KG QAS. We then use our findings to simulate whether a variety of different potential quality enhancement strategies would be consistently targeted.

The results, comparing the two tools, are relatively consistent in terms of national averages, suggesting the QAS provides valuable information for national action. On the classroom, school, and district levels, consistency is lower. Consistency varies by the dimension of quality and data collection methods used, with direct measures of child development outcomes or easily observable characteristics, such as class sizes, showing more consistency. There are relatively few relationships between consistency and school or class characteristics, which bodes well for equitable implementation. Moreover, consistency is similar with ministry employees as with professional data collectors, who were randomized across districts. This result is promising for cost-effective national scale up. However, the limited consistency of many items and dimensions means that targeted quality enhancement actions often would target different schools using the two different measures. The results underscore how QAS are best implemented as a formative system, a starting point for quality enhancement, and not as a summative system that directly punishes or rewards specific schools, classes, or teachers.

# **2 Background**

# **_2.1 What we know about education quality assurance systems_**

QAS (for pre-primary and otherwise) have three main components: (1) quality standards, (2) tools for monitoring whether standards are being met, and (3) quality enhancement actions that follow from the results of the monitoring tool (Raikes, Neuman, and Burton 2019). As a concrete example, consider a pre-primary quality standard that teaching should be play-based. The monitoring tool would then, in this case likely using a classroom observation tool, collect data on whether a play-based pedagogy was being implemented. If the monitoring tool data indicated a teacher was not using play-based pedagogy, a potential quality enhancement action would be providing the teacher training on play-based pedagogy. Although this is the ideal tripartite system, it is important to note that countries may not have all these components in place; for instance in a recent study on pre-primary QAS in Africa, countries usually had at least one component of standards or tools, but only some had all components in place (Raikes, Sayre, and Lima 2021). There is particularly limited comprehensive information globally about quality enhancement components of QAS. While the SABER-ECD database includes 38 countries and looks at monitoring and standards for pre-primary QAS, it does not look at quality enhancement 3