The Role of Anomalous Data in Knowledge Acquisition: A Theoretical Framework and Implications for Science Instruction

TLDR

Science students’ reactions to anomalous data are key to understanding knowledge acquisition in classrooms. The article analyzes scientists’ and students’ responses to anomalous data and discusses implications for science instruction. The authors propose seven response forms to anomalous data—one accepting and six discounting—and analyze factors that influence which form is chosen, especially those favoring theory change.

Abstract

Understanding how science students respond to anomalous data is essential to understanding knowledge acquisition in science classrooms. This article presents a detailed analysis of the ways in which scientists and science students respond to such data. We postulate that there are seven distinct forms of response to anomalous data, only one of which is to accept the data and change theories. The other six responses involve discounting the data in various ways in order to protect the preinstructional theory. We analyze the factors that influence which of these seven forms of response a scientist or student will choose, giving special attention to the factors that make theory change more likely. Finally, we discuss the implications of our framework for science instruction.