Category change in the absence of cognitive conflict.

Abstract

Category Change in the Absence of Cognitive ConflictLearning that adds new knowledge to the learner's memory with little or no change in prior knowledge is monotonic. The learner's knowledge base grows steadily. If the learner has little prior knowledge of the relevant subject matter, this view serves as a first approximation. But when the learner already has some knowledge of the relevant subject matter and, moreover, new information contradicts that prior knowledge, then learning might involve complicated interactions between the two (Chinn & Brewer, 1993). If the learner must override or reject his or her prior knowledge, his or her knowledge base shrinks as well as grows, so learning is nonmonotonic (Ohlsson, 2011). Cognitive change of this latter sort is variously referred to as attitude change, belief revision, conceptual change, restructuring, theory change, and deep learning (Ohlsson, 2011). In this article, we adhere to the usage that has become common in the learning sciences and call it conceptual change.There are multiple theories of the cognitive processes involved in conceptual change. Özdemir and Clark (2007) distinguish between knowledge-as-theory perspectives and knowledge-as-elements perspectives. Theories in the former category conceptualize intuitive and informal knowledge as theory-like in character, and the process of change consequently shares structural features with theory change in science (

Consumer Decision-Making Based on Review Websites: Are There Differences Between Choosing a Hotel and Choosing a Physician?

“…In the interviews after the choice tasks, participants’ conceptualization of the two websites appeared entirely different. The themes that emerged from our interviews describe this sense-making process or, consistent with resubsumption [ 24 , 25 ] and recategorization theory [ 27 , 29 ], the change from monotonic processing (both websites are the same and should be approached equally) to nonmonotonic change (the differences between the 2 choices outweigh the similarities and therefore the decision-making process for the 2 choice changes).…”

“…Resubsumption [ 24-27 ] and recategorization theory [ 27 , 28 ] outline how individuals reason when they encounter new phenomena, when they apply the same frame of logic that they learned from a similar earlier experience (monotonic processing) or a different one (nonmonotonic learning). Monotonic processes entail the learning of new information without any changes to the existing knowledge, whereas nonmonotonic learning coincides with changes in cognition, such as in attitudes, beliefs, conceptual or theory change, or deep learning [ 26 , 29 ]. Therefore, when individuals are faced with new situations or information, they by default anchor what they see, read, or perceive monotonically into a scheme that they are already familiar with [ 25 ].…”

Relational discovery in category learning.

“…Still, beyond the complexity of real-world relational categories and learning environments, a perhaps bigger challenge to learning is the conflicting conceptual understanding students bring to bear to many educational contexts, especially in science (e.g., Chi, Roscoe, Slotta, Roy, & Chase, 2012; Jacobson, Kapur, So, & Lee, 2010). Goldwater and Schalk (2016) argue that a crucially underexplored research area is building laboratory-models of conceptual change by implementing multiphase category learning experiments where there are conflicts between earlier and later phases (see Ramsburg & Ohlsson, 2016; Sewell & Lewandowsky, 2011 for work along these lines), and then applying such models to the classroom. Real-world concepts are interrelated, forming conceptual systems.…”

Variable control and conceptual change: A large-scale quantitative study in elementary school

“…Thus, if misconceptions might interfere with students' initial learning, in the long run it can be beneficial to discuss and reflect as many initial conceptions as possible (Kapur & Rummel, 2012). This can trigger powerful knowledge changes even if students' initial knowledge comprises primarily misconceptions (Ramsburg & Ohlsson, 2016). Our analytic approach -latent transition analysis -offers valuable information on how to target specific groups of students.…”