منابع مشابه
Blocking in category learning.
Many theories of category learning assume that learning is driven by a need to minimize classification error. When there is no classification error, therefore, learning of individual features should be negligible. The authors tested this hypothesis by conducting three category-learning experiments adapted from an associative learning blocking paradigm. Contrary to an error-driven account of lea...
متن کاملCategory use and category learning.
Categorization models based on laboratory research focus on a narrower range of explanatory constructs than appears necessary for explaining the structure of natural categories. This mismatch is caused by the reliance on classification as the basis of laboratory studies. Category representations are formed in the process of interacting with category members. Thus, laboratory studies must explor...
متن کاملCategory structure modulates interleaving and blocking advantage in inductive category acquisition
Research in inductive category learning has demonstrated that interleaving exemplars of categories results in better performance than presenting each category in a separate block. Two experiments indicate that the advantage of interleaved over blocked presentation is modulated by the structure of the categories being presented. More specifically, interleaved presentation results in better perfo...
متن کاملProbabilistic category learning 1 RUNNING HEAD: Probabilistic category learning Challenging the Role of Implicit Processes in Probabilistic Category Learning
Considerable interest in the hypothesis that different cognitive tasks recruit qualitatively distinct processing systems has led to the proposal of separate explicit (declarative) and implicit (procedural) systems. A popular probabilistic category learning task known as the “Weather Prediction Task” is said to be ideally suited to examine this distinction because its two versions – ‘observation...
متن کاملDynamical trajectories in category learning.
Category learning has traditionally been studied by examining how percentage correct changes with experience (i.e., in the form of learning curves). An alternative and more powerful approach is to examine dynamical learning trajectories--that is, to examine how the parameters that describe the current state of the model change with experience. We describe results from a new experimental paradig...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Experimental Psychology: General
سال: 2007
ISSN: 1939-2222,0096-3445
DOI: 10.1037/0096-3445.136.4.685