Science and Technology Production
Proceedings of the 39th Annual Conference of the Cognitive Science Society - Promoting Spontaneous Analogical Transfer by Idealizing Target Representations

Congress

Authorship
TRENCH, JUAN MAXIMO ; MICAELA TAVERNINI ; ROBERT GOLDSTONE
Date
2017
Publishing House and Editing Place
Cognitive Science Society
ISSN
978-0-9911967-6-0
Summary Information provided by the agent in SIGEVA
Recent results demonstrate that inducing an abstract representation of target analogs at retrieval time aids access to analogous situations with mismatching surface features (i.e., the late abstraction principle). A limitation of current implementations of this principle is that they either require the external provision of target-specific information or demand very high intellectual engagement. Experiment 1 demonstrated that constructing an idealized situation model of a target problem increas... Recent results demonstrate that inducing an abstract representation of target analogs at retrieval time aids access to analogous situations with mismatching surface features (i.e., the late abstraction principle). A limitation of current implementations of this principle is that they either require the external provision of target-specific information or demand very high intellectual engagement. Experiment 1 demonstrated that constructing an idealized situation model of a target problem increases the rate of correct solutions compared to constructing either concrete simulations or no simulations. Experiment 2 confirmed that these results were based on an advantage for accessing the base analog, and not merely on an advantage of idealized simulations for understanding the target problem in its own terms. This target idealization strategy has broader applicability than prior interventions based on the late abstraction principle, because it can be achieved by a greater proportion of participants and without the need to receive target-specific information.
Show more Show less
Key Words
IDEALIZATIONTRANSFERANALOGYRETRIEVAL