Randomized controlled trials (RCTs) in education are common as the design allows for an unbiased estimate of the overall impact of a program. As more RCTs are completed, researchers are also noting that an overall average impact may mask substantial variation across sites or groups of individuals. Mixed methods can provide insight and help in unpacking some of the reasons for these variations in impact. This article contributes to the field of mixed methods research by integrating mixed methods into a recently developed conceptual framework for understanding variations in impact. We model the use of this approach within the context of an RCT for online courses that found differences in impact across courses.

教育领域的随机对照试验 (RCT) 很常见，因为其设计允许对项目的整体影响进行无偏估计。随着更多 RCT 的完成，研究人员还注意到，总体平均影响可能会掩盖不同地点或个人群体之间的重大差异。混合方法可以提供洞察力并帮助解开这些影响变化的一些原因。本文通过将混合方法整合到最近开发的用于理解影响变化的概念框架中，为混合方法研究领域做出了贡献。我们在 RCT 的背景下对这种方法的使用进行建模，该在线课程发现不同课程的影响存在差异。