||**Overall**|0.978|
|---|---|---|
|**Teach ECE**|Classroom Culture|0.651|
||Guided Learning|0.820|
||Socio-Emotional Skills|0.771|
||**Overall**|0.889|

# **Analysis**

Given the sampling design, results do not require weighting to be representative of the PCHIP project area. In addition, on reporting the results of composite items calculated as described above, we also present results based on the proportion of **segments** demonstrating a certain degree of quality and the proportion of **children** with different skills. Below, we outline the process used to set benchmarks needed to dichotomize these results on AIM-ECD and Teach ECE. In addition to the simple descriptive statistics and disaggregation, we also build a statistical model for inferential purposes. The details of this model-building process are outlined below.

# **_Quality Benchmarks, Exemplar Items, and Standardized Scores_**

As described above, both the AIM-ECD DA and Teach ECE generate continuous scores to describe child developmental outcomes and quality of teaching practices, respectively. AIMECD scores range from 0-100% while Teach ECE element and area scores range from 1-5.

These continuous scores are limited in their comprehensibility. To improve the communicability of our results, we also utilize benchmarks on Teach ECE to report on how much of the time (i.e., what proportion of segments) classrooms are demonstrating minimal quality during lessons. When reporting on the proportion of segments demonstrating minimum quality, we use the proportion of segments that received at least a “Medium” rating, i.e., an average rating of at least 3. Three represents the score achieved by a class with no extremely serious quality issues and thus is a reasonably interpretable benchmark. Teach ECE quality benchmarks are useful for creating concrete descriptives about the status of ECD in South Punjab but should not be interpreted as the result of best practice standards recommended for external use.<sup>5</sup> We do not set similar benchmarks for AIM-ECD that allow us to talk about the proportion of children demonstrating minimal developmental levels. Instead, we report the results from a set of exemplar items on the assessment to describe the proportion of children able to accomplish certain skills.

In addition to using quality benchmarks for Teach ECE and exemplar items AIM-ECD, we also transform AIM-ECD and Teach ECE continuous scores to improve interpretability of our multiple regression analysis. We transform both scores to a standardized variable with mean 0 and standard deviation 1 (i.e., Z-scores). This allows us to interpret coefficients from our models as differences in outcome standard deviations (for AIM-ECD scores) and in teaching quality (for

> 5 Standard setting is a complex normative process that requires buy-in from relevant stakeholders and experts, careful consideration of what children “should” be able to do at a given age or stage of education, and an examination of the consequences of these decisions (American Educational Research Association et al., 2014; Cizek & Bunch, 2007). A formal standard setting exercise to provide additional meaning to AIM-ECD DA and Teach ECE scores is currently under consideration and will be part of the public set of resources available for users of these tools.

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