Making probabilistic relational categories learnable

Kittur, Hummel and Holyoak (2004) showed that people have great difficulty learning relation-based categories with a probabilistic (i.e., family resemblance) structure. In Experiment 1, we investigated interventions hypothesized to facilitate learning family-resemblance relational categories. Changing the description of the task from learning about categories to choosing the “winning” object in each stimulus had the greatest impact on subjects’ ability to learn probabilistic relation-based categories. Experiment 2 tested two hypotheses about how the “who’s winning” task works. The results are consistent with the hypothesis that the task invokes a “winning” schema that encourages learners to discover a higher-order relation that remains invariant over members of a category. Experiment 3 reinforced and further clarified the nature of this effect. 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.

Name thesis:degree_name

M.A.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Psychology

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2013

Author dc:creator

• Jung, Wookyoung

Contributors dc:contributor

• Hummel, John E.
• Ross, Brian H.

• Relational category learning
• family resemblance
• higher-order relations
• relational invariants
• who’s winning task

Statement dc:rights

• Copyright 2012 Wookyoung Jung

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/42228

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/42228