Category learning with minimal prior knowledge.

Abstract

In 6 experiments, the authors examined the use of prior knowledge in category learning. Previous studies of the effects of knowledge on category learning have used categories in which knowledge was related to all of the category's features. However, people's knowledge of real-world categories often consists of many "rote" features that are not related to their prior knowledge. Five experiments found that even minimal prior knowledge (1 knowledge-relevant feature and 5 rote features per exemplar) can facilitate category learning. Posttests revealed that although the knowledge aided learning, subjects also acquired the rote features that were not related to knowledge, contradicting predictions of an attentional explanation of the knowledge effect. The results of Experiment 6 suggested that subjects attempt to link even rote features to their knowledge. When people learn a new category, they are influenced by both the properties of the observed category exemplars and their knowledge about the category's domain. Learning is easier when prior knowledge is consistent with a category that is to be learned than when knowledge is inconsistent or simply absent (Murphy & Allopenna, 1994; Pazzani, 1991; Wattenmaker, Dewey, T. Murphy, & Medin, 1986). By prior knowledge we mean knowledge about a broad domain, such as animals, birds, vehicles, or computers, that exists before learning a new category. This knowledge connects features of a new category, perhaps through causal relations, and provides some sort of explanation of why the category has the properties it does (see Carey, 1985; Keil, 1989; Murphy, 1993, in press; Murphy & Medin, 1985). To give a very simple example: People have some idea about how animals fly that provides a possible explanation for why something that has wings can live high on a cliff-the wings explain flying, which in turn explains why this habitat is possible. Such prior knowledge contrasts with category structure: empirical or statistical information about a category of the sort "most of the category members have wings" or "one of the exemplars has a red back, wings, and three legs." Both sources of information are used in much category learning, as one cannot rely solely on prior knowledge in learning something new, and yet such knowledge can greatly speed learning when it is correct. One of the main issues facing the psychology of concepts is to understand how prior knowledge influences category learning. Although it seems intuitively obvious that such knowledge can aid

La Edad Se Correlaciona Directamente con la Fuerza de los Estereotipos de Género: Evidencia Obtenida en una Tarea de Memoria de Reconocimiento

“…En algunos casos el concepto puede hacer el procesamiento más eficiente. Por ejemplo, durante el aprendizaje de un concepto nuevo, el hecho de poseer un concepto previo relacionado lo hace más fácil de aprender (Clapper, 2007;Hoffman, Harris & Murphy, 2008;Kaplan & Murphy, 2000;Murphy & Allopenna, 1994). Sin embargo, y al mismo tiempo, poseer un concepto puede introducir errores o sesgos (e.g., Elischberger, 2005).…”

Blocking in category learning.

“…Moreover, Kaplan and Murphy's (2000) results suggest that learning is not entirely error-driven when themed categories are used. Kaplan and Murphy taught one group of participants novel categories in which some but not all of the exemplar features were connected by a prior knowledge theme.…”

The importance of being coherent: Category coherence, cross-classification, and reasoning☆

“…''Lives in water, eats fish, has many offspring, is small'' describes a more coherent category than ''lives in water, eat wheat, has a flat end, is used for stabbing bugs'' (Murphy & Wisniewski, 1989). It is well documented that most natural categories are at least somewhat coherent (Ahn, 1998;Keil, 1989;Malt & Smith, 1984;Sloman, Love, & Ahn, 1998), and that coherence of novel categories influences ease of learning and use (Heit & Bott, 2000;Kaplan & Murphy, 2000;Lin & Murphy, 2001;Murphy & Allopenna, 1994;Pazzani, 1991;Rehder & Ross, 2001;Spalding & Murphy, 1996;Wattenmaker, Dewey, Murphy, & Medin, 1986;Wisniewski, 1995).…”

“…''Lives in water, eats fish, has many offspring, is small'' describes a more coherent category than ''lives in water, eat wheat, has a flat end, is used for stabbing bugs'' (Murphy & Wisniewski, 1989). It is well documented that most natural categories are at least somewhat coherent (Ahn, 1998;Keil, 1989;Malt & Smith, 1984;Sloman, Love, & Ahn, 1998), and that coherence of novel categories influences ease of learning and use (Heit & Bott, 2000;Kaplan & Murphy, 2000;Lin & Murphy, 2001;Murphy & Allopenna, 1994;Pazzani, 1991;Rehder & Ross, 2001;Spalding & Murphy, 1996;Wattenmaker, Dewey, Murphy, & Medin, 1986;Wisniewski, 1995).The relations that make features ''go together'' can be causal (Ahn, 1998;Rehder & Hastie, 2001, 2004 (Barsalou, 1983(Barsalou, , 1985. While all facilitate learning, there is some evidence that a common cause structure, one in which a few causal features give rise to many effect features, results in especially high category coherence (Ahn, 1998;Ahn, Kim, Lassaline, & Dennis, 2000; but see Rehder & Hastie, 2004;Sloman et al, 1998).…”