This article estimates, for a sample of 1,777 Syrian refugee children, the impact on basic reading assessments of attending a remedial support program in Lebanon that was infused with social and emotional learning practices. We use flexible methods that capitalize on advantages of both machine learning and Bayesian inferential frameworks to leverage the information available in understudied contexts and help account for the problem of self-selection. Average treatment effects were estimated both using multiply imputed data and data from outcome-respondents only. We do not find conclusive evidence for an effect on one of the reading measures studied (ASER). However, we provide evidence for positive effects for three, more robust, measures of basic reading outcomes from the Arabic EGRA assessment. We discuss potential reasons for the differences in effects that are relevant for educational research and practice. We also consider the implications for future research of choices related to measurement, data collection and processing, and missing data.
翻译:对抽样的1 777名叙利亚难民儿童来说,这一条款估计,参加黎巴嫩的补救性支持方案在社会和情感上学习的做法,对基本阅读评估的影响。我们使用灵活方法,利用机器学习和巴伊西亚推论框架的优势,利用在研究不足的情况下可获得的信息,帮助说明自我选择问题。平均治疗效果仅使用乘数估算数据和结果答复者提供的数据来估计。我们没有发现对所研究的阅读措施之一产生影响的确凿证据(ASER)。然而,我们提供了证据,说明三项更强有力的阿拉伯EGRA评估基本阅读结果措施的积极效果。我们讨论了与教育研究和实践有关的效果差异的潜在原因。我们还审议了与衡量、数据收集和处理以及缺失数据有关的选择对未来研究的影响。