Feature centrality and property induction

A feature is central to a concept to the extent that other features depend on it. Four studies tested the hypothesis that people will project a feature from a base concept to a target concept to the extent that they believe the feature is central to the two concepts. This centrality hypothesis implies that feature projection is guided by a principle that aims to maximize the structural commonality between base and target concepts. Participants were told that a category has two or three novel features. One feature was the most central in that more properties depended on it. The extent to which the target shared the feature’s dependencies was manipulated by varying the similarity of category pairs. Participants’ ratings of the likelihood that each feature would hold in the target category support the centrality hypothesis with both natural kind and artifact categories and with both well-specified and vague dependency structures.     

Conceptual Knowledge,Procedural Knowledge,and Metacognition in Routine and Nonroutine Problem Solving

When, how, and why students use conceptual knowledge during math problem solving is not well understood. We propose that when solving routine problems, students are more likely to recruit conceptual knowledge if their procedural knowledge is weak than if it is strong, and that in this context, metacognitive processes, specifically feelings of doubt, mediate interactions between procedural and conceptual knowledge. To test these hypotheses, in two studies (Ns = 64 and 138), university students solved fraction and decimal arithmetic problems while thinking aloud; verbal protocols and written work were coded for overt uses of conceptual knowledge and displays of doubt. Consistent with the hypotheses, use of conceptual knowledge during calculation was not significantly positively associated with accuracy, but was positively associated with displays of doubt, which were negatively associated with accuracy. In Study 1, participants also explained solutions to rational arithmetic problems; using conceptual knowledge in this context was positively correlated with calculation accuracy, but only among participants who did not use conceptual knowledge during calculation, suggesting that the correlation did not reflect “online” effects of using conceptual knowledge. In Study 2, participants also completed a nonroutine problem-solving task; displays of doubt on this task were positively associated with accuracy, suggesting that metacognitive processes play different roles when solving routine and nonroutine problems. We discuss implications of the results regarding interactions between procedural knowledge, conceptual knowledge, and metacognitive processes in math problem solving.