Performed 4 experiments to determine whether linearly separable (LS) categories (which can be perfectly partitioned on the basis of a weighted, additive combination of component information) are easier to learn than non-LS categories. 224 Ss, predominantly undergraduates, participated. Independent cue models (e.g., prototype theories) predict that, with average between-category similarity held constant, LS categories will be easier to master. Relational coding models (e.g., the context model) imply that individual cases of high similarity of exemplars to exemplars in contrasting categories are the major determinant of task difficulty. These experiments varied stimulus type (geometric shapes or photographs of faces), category size (small or infinitely large), and instructions. With average similarity controlled, instances of high similarity of exemplars to exemplars influenced performance, but there was no evidence that LS categories were learned more readily than non-LS categories. (29 ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved).
|Original language||English (US)|
|Number of pages||14|
|Journal||Journal of Experimental Psychology: Human Learning and Memory|
|State||Published - Sep 1 1981|
- category size &
- instructions, classification learning, college students
- linear separability of stimulus category type &