Mechanistic reasoning, or reasoning systematically through underlying factors and relationships that give rise to phenomena, is a powerful thinking strategy that allows one to explain and make predictions about phenomena. This article synthesizes and builds on existing frameworks to identify essential characteristics of students’ mechanistic reasoning across scientific content areas. We argue that these characteristics can be represented as epistemic heuristics, or ideas about how to direct one’s intellectual work, that implicitly guide mechanistic reasoning. We use this framework to characterize middle school students’ written explanatory accounts of two phenomena in different science content areas using these heuristics. We demonstrate evidence of heuristics in students’ accounts and show that the use of the heuristics was related to but distinct from science content knowledge. We describe how the heuristics allowed us to characterize and compare the mechanistic sophistication of account construction across science content areas. This framework captures elements of a crosscutting practical epistemology that may support students in directing the construction of mechanistic accounts across content areas over time, and it allows us to characterize that progress.

机械推理或通过引起现象的潜在因素和关系进行系统推理，是一种强大的思维策略，可以使人们对现象进行解释和做出预测。本文综合并建立在现有框架的基础上，以跨科学内容领域确定学生机械推理的基本特征。我们认为这些特征可以表示为认知启发式或有关如何指导自己的智力工作的想法，这些想法暗含了指导机械推理的作用。我们使用这种启发式方法，使用不同的科学来描述中学生在不同科学内容领域对两种现象的书面解释性描述。我们在学生的账目中证明了启发式方法的证据，并表明启发式方法的使用与科学内容知识相关但又有所不同。我们描述了启发式方法如何使我们能够表征和比较跨科学内容领域的帐户构建机制的复杂性。该框架捕获了贯穿各领域的实践认识论的要素，这些要素可能会随着时间的流逝而支持学生指导跨内容领域的机制帐户的构建，并且它使我们能够表征这一进展。