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2 The Role of Causality in Understanding How Prior Event Knowledge Impacts New Learning

Published online by Cambridge University Press:  21 December 2023

Alexa S. Gonzalez*
Affiliation:
Villanova University, Villanova, PA, USA. University of Houston, Houston, TX, USA
Anna B. Drummey
Affiliation:
Villanova University, Villanova, PA, USA.
Tyler J. Hubeny
Affiliation:
Villanova University, Villanova, PA, USA.
Alexander Held
Affiliation:
Villanova University, Villanova, PA, USA.
Irene P. Kan
Affiliation:
Villanova University, Villanova, PA, USA.
*
1Correspondence: Alexa S. Gonzalez, Department of Psychological & Brain Sciences, Villanova University, agonza49@villanova.edu
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Abstract

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Objective:

The influence of prior knowledge on new learning is well established. However, there has been less research dedicated to teasing apart the key components of prior knowledge’s structure that contribute to memory enhancement. In the current study, we focused on event structures, which include various relations, such as associative, causal, and temporal. Given that events possess attributes relevant to numerous cognitive memory processes, we were most interested in exploring how event structures that possess causal relations enhance new memory formation. Specifically, we examined whether events that exhibit causal associative relations provide an additional boost to new learning compared to event structures with non-causal associative relations.

Participants and Methods:

Forty-six undergraduate students took part in the study. Participants’ learning of the content of image pairs that exhibit everyday, real-world events were measured using a cued recall paradigm. The stimuli consisted of 60 image pairs that illustrated two events that were related causally and associatively (i.e., causal pairs); related only associatively (i.e., non-causal pairs); or not related at all (i.e., unrelated pairs). During an encoding phase, image pairs were presented one at a time, and after the presentation of each image pair, participants answered an encoding question that focused on the relationship between the two images. After the encoding phase and a short filler task, participants were shown a cue image (always the first picture from the pair) and were asked to provide a brief written description of the content of the second presented image from each pair. Also, as a manipulation check, we asked subjects to rate each image pair on causal direction and association strength after completion of the cued recall memory task.

Results:

We found that, relative to unrelated pairs, events that possess associative relations (i.e., both causal and non-causal items) benefit learning of new information. In addition, causal relations provided an additional boost to new learning. Specifically, cued recall performance is best for causal pairs, followed by non-causal pairs and unrelated pairs. Moreover, causal direction ratings significantly predict overall itemlevel accuracy above and beyond general associative relations that exist in events. We also examined recall accuracy for specific content information within each event (i.e., agent, action, object) and found that causal relations uniquely contribute to recall performance of objects and actions.

Conclusions:

Overall, the present study’s findings suggest that prior event knowledge structures possessing causal and non-causal associative relations support new learning, especially compared to image pairs with no relations. Of interest, causality provides an additional boost to new learning above and beyond general associative relations. By focusing on the role of causality in event structures, our findings informed our understanding of how prior knowledge supports new learning. Considering that the effect of prior knowledge on new episodic learning is especially evident in older adults, since they more readily rely on their schematic knowledge, a future direction would entail investigating how causal links influence new memory formation in older adults.

Type
Poster Session 01: Medical | Neurological Disorders | Neuropsychiatry | Psychopharmacology
Copyright
Copyright © INS. Published by Cambridge University Press, 2023