Large-scale education interventions aimed at diminishing disparities and generating equitable learning outcomes are often complex, involving multiple components and intended impacts. Evaluating implementation of complex interventions is challenging because of the interactive and emergent nature of intervention components. Methods that build from systems science have proven useful for addressing evaluation challenges in the complex intervention space. Complexity science shares some terminology with systems science, but the primary aims and methods of complexity science are different from those of systems science. In this paper we describe some of the language and ideas used in complexity science. We offer a set of priorities for evaluation of complex interventions based on language and ideas used in complexity science and methodologies aligned with the priorities.

旨在缩小差距和产生公平学习成果的大规模教育干预措施通常很复杂，涉及多个组成部分和预期影响。由于干预组成部分的交互性和紧急性，评估复杂干预的实施具有挑战性。从系统科学构建的方法已被证明可用于解决复杂干预空间中的评估挑战。复杂性科学与系统科学共享一些术语，但复杂性科学的主要目标和方法不同于系统科学。在本文中，我们描述了复杂性科学中使用的一些语言和思想。