Identifying Essential Epistemic Heuristics for Guiding Mechanistic Reasoning in Science Learning

Christina Krist, Christina V. Schwarz, Brian J. Reiser

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)160-205
Number of pages46
JournalJournal of the Learning Sciences
Issue number2
StatePublished - Mar 15 2019

ASJC Scopus subject areas

  • Education
  • Developmental and Educational Psychology


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