ERIC Number: EJ1069850
Record Type: Journal
Publication Date: 2015-Aug
Abstractor: As Provided
Reference Count: N/A
Making Probabilistic Relational Categories Learnable
Jung, Wookyoung; Hummel, John E.
Cognitive Science, v39 n6 p1259-1291 Aug 2015
Theories of relational concept acquisition (e.g., schema induction) based on structured intersection discovery predict that relational concepts with a probabilistic (i.e., family resemblance) structure ought to be extremely difficult to learn. We report four experiments testing this prediction by investigating conditions hypothesized to facilitate the learning of such categories. Experiment 1 showed that changing the task from a category-learning task to choosing the "winning" object in each stimulus greatly facilitated participants' ability to learn probabilistic relational categories. Experiments 2 and 3 further investigated the mechanisms underlying this "who's winning" effect. Experiment 4 replicated and generalized the "who's winning" effect with more natural stimuli. Together, our findings suggest that people learn relational concepts by a process of intersection discovery akin to schema induction, and that any task that encourages people to discover a higher order relation that remains invariant over members of a category will facilitate the learning of putatively probabilistic relational concepts.
Descriptors: Schemata (Cognition), Concept Formation, Probability, Educational Experiments, Hypothesis Testing, Task Analysis, Learning Processes, Thinking Skills
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Sponsor: US Air Force (DOD), Office of Scientific Research (AFOSR)
Authoring Institution: N/A