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Updated: May 25, 2025

A Method to Quantify Visual Information Processing in Children Using Eye Tracking
Published on: July 9, 2016
Identifying similarity- and rule-based processes in quantitative judgments: A multi-method approach combining
Florian I Seitz1, Rebecca Albrecht2,3, Bettina von Helversen4
1Center for Economic Psychology, Department of Psychology, University of Basel, Missionsstrasse 62a, 4055, Basel, Switzerland. florian.seitz@unibas.ch.
Abstract:
Quantitative judgments have been suggested to result from a mixture of similarity- and rule-based processing. People can judge an object's criterion value based on the object's similarity to previously experienced exemplars and based on a rule that integrates the object's cues like a linear regression. In order to better understand these processes, the present work combines cognitive modeling and eye tracking and tests whether people who rely more on the similarity to exemplars also look more at the exemplar locations on the screen. In two eye-tracking studies, participants learned to assign each of four exemplars to a different screen corner and criterion value and then judged the criterion value of briefly presented test stimuli. Eye tracking measured participants' gazes to the now empty exemplar locations (a phenomenon called looking-at-nothing); cognitive modeling of the test phase judgments quantified participants' reliance on a similarity- over a rule-based process. Participants showed more similarity use and more looking-at-nothing in the study in which the cues were linked to the criterion by a multiplicative function than in the study with an additive cue-criterion link. Focusing on the study with a multiplicative environment, participants relying more on the similarity to exemplars also showed more looking-at-nothing ( = 0.25, p = .01). Within trials, looking-at-nothing was usually directed at the one exemplar that was most similar to the test stimulus. These results show that a multi-method approach combining process tracing and cognitive modeling can provide mutually supportive insights into the processes underlying higher-order cognition.
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