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

Abstract

Understanding how science students respond to anomalous data is essential to understanding knowledge acquisition in science classrooms. In this report, we present a detailed analysis of the ways in which scientists and science students respond to anomalous 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.Anomalous Data -2 THE ROLE OF ANOMALOUS DATA IN KNOWLEDGE ACQUISITION: A THEORETICAL FRAMEWORK AND IMPLICATIONS FOR SCIENCE INSTRUCTIONThis report addresses an issue that is crucial for understanding how people learn science and how to improve science instruction: How do students respond when they encounter scientific information that contradicts their current theories' about the physical world? In other words, how do students respond when their current beliefs about the physical world conflict with the information presented during science instruction?This issue is crucial for two reasons. The first is that encountering contradictory information is a very common occurrence when one is learning science. Science students' preinstructional beliefs about the natural world often conflict sharply with many of the accepted scientific theories they are taught in school, and this is true across a wide variety of domains within biology, chemistry, and physics (for reviews, see Carey, 1985;Champagne, Klopfer, & Gunstone, 1982;Confrey, 1990;Driver & Easley, 1978; Driver, Guesne, & Tiberghien, 1985;Eylon & Linn, 1988;Osborne & Freyberg, 1985;Perkins & Simmons, 1988;Roth, 1990). Thus, the encounter with contradictory information is at the heart of knowledge acquisition in science.The second reason why understanding how students respond to contradictory information is crucial for science education is that students typically resist giving up their preinstructional beliefs. Instead of abandoning or modifying their preinstructional beliefs in the face of new, conflicting data and ideas, students often staunchly maintain old ideas and reject or distort new ideas. For instance, some children who are told that the earth is round preserve their preinstructional belief that the earth is flat by concluding that the earth is disc shaped (Vosniadou & Brewer, 1992). Similarly, children can spend days or weeks studying photosynthesis and yet persist in their preinstructional belief that plants get their food from the soil (Anderson & Smith, 1984). And a number of researchers have found that many young adults go through high school and university physics courses without ever giving up their pre-Newtonian views of motion (e.g., Champagne, Klopfer, & Anderson...

Invited Lectures from the 13th International Congress on Mathematical Education

“…This is consistent with intuitive application of fuzzy logic (e.g., Zazkis 1995) to a mathematical situation. Further, prime numbers were the most notable exceptions from the perceived 'rule', which is in accord with Chinn and Brewer (1993) category of "excluding data from the currently held theory", as is exemplified below.…”

“…Clyde: I wasn't sure myself either, I just didn't want you to think you were right so I denied it. Students' tendency to reject evidence that is not in accord with their held beliefs was noted in several studies (e.g., Chinn and Brewer 1993;Edwards 1997). Given that script-writers were prospective teachers, this tendency of their script characters exemplifies their awareness of such behavior among students.…”

“…As such, even when a mathematically correct conclusion was drawn, some participants attempted to amend the theory by referring to a limited scope of applicability. Theory amendment is in accord with a mathematical/scientific norm in response to disconfirming evidence (Chinn and Brewer 1993), however, the amendment itself was usually incorrect. For example, consider the following views included in the commentary: "Large numbers do not always have more factors.…”

“…Attention to large numbers is an additional extension to the list of responses to "anomalous data" identified by Chinn and Brewer (1993): rechecking the evidence with additional and more convincing examples. Perhaps this extension is applicable to mathematics settings more than science settings.…”

Detangling the Interrelationships Between Self-Regulation and Ill-Structured Problem Solving in Problem-Based Learning

“…While an appropriate response would be to evaluate the alignment between experimental findings and hypotheses, reflect on causes, and make necessary adjustments, Chinn and Brewer (1993) found that learners would discount anomalous data in various ways to defend their original theory. Researchers have linked such behaviors to learners' epistemic beliefs (e.g., Pintrinch, Marx, & Boyle, 1993;Qian & Alverman, 1995;Windschitl & Andre, 1998).…”