Abstract

Panel data methods, which include difference-in-differences and comparative interrupted time series, have become increasingly common in education policy research. The key idea is to use variation across time and space (e.g., school districts) to estimate the effects of policy or programmatic changes that happen in some localities but not others. In this commentary we highlight some specific challenges for panel or longitudinal studies of K-12 education interventions during and following the COVID-19 pandemic. Our goal is to help researchers think through the underlying issues and assumptions, and to help consumers of those studies assess their validity.

摘要

面板数据方法，包括差异中的差异和比较中断的时间序列，在教育政策研究中变得越来越普遍。关键思想是使用跨时间和空间（例如，学区）的变化来估计发生在某些地方而不是其他地方的政策或计划变化的影响。在本评论中，我们强调了 COVID-19 大流行期间和之后 K-12 教育干预的小组或纵向研究面临的一些具体挑战。我们的目标是帮助研究人员思考潜在的问题和假设，并帮助这些研究的消费者评估其有效性。