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• W2406288889 abstract "Using eye-tracking to predict children's success or failure on analogy tasks Robert M. French and Jean-Pierre Thibaut {robert.french, jean-pierre.thibaut}@u-bourgogne.fr LEAD-CNRS, UMR 5022, University of Burgundy, Pole AAFE – Esplanade Erasme 21065 DIJON. FRANCE Abstract analogy-making abilities in children. One of the first developmental analogy-making studies was one by We use eye-tracking data, analyzed by a neural network and by Linear Discriminant Analysis (LDA), to study the temporal dynamics of children's analogy making. We determine how well the number of item-to-item saccades while solving an analogy problem predicts whether or not a child will correctly answer the problem. For the A:B::C:D visual analogy problems, by the first third of the trial we can tell with 64% accuracy whether or not the problem will be answered correctly. Two-thirds of way through the trial, we can predict with 82% accuracy the answer that will be given. By looking only at the final third of the trial, we can predict with up to 90% accuracy what the child will do. Average gaze times at the Target and Distractor items have the same predictive power as the item-to-item saccade information. A B Possible answers : C Figure 1. The type of A:B::C:? analogy problems used in the present study Keywords: Analogical reasoning; development; eye-tracking; strategies, prediction in analogy making Introduction The centrality of analogical reasoning to human cognition is not open to debate (Gentner & Smith, 2012; Holyoak, 2012). On the other hand, there are many open questions surrounding how analogy making occurs and how the ability to do analogies develops over time. Very little work has been done on the dynamics of solving analogy problems. The vast majority of experiments involve selecting particular items as the solution to an analogy problem. This is a static approach to analogy making and, by definition, cannot address the issue of how a strategy evolves during an attempt to solve a problem. For a number of years, we have used eye-tracking technology to study analogy-making strategies, particularly in children. As an analogy problem is being solved, the information sought and manner in which it is sought can be elucidated by the visual strategies by the problem solver. The amount of attention paid to a particular item and the gaze-fixation on that item have been shown to be highly correlated, in particular, for complex stimuli (Deubel & Schneider, 1996; He & Kowler, 1992). In addition, the fixation time associated with a given item correlates with its informativeness (Nodine, Carmody, & Kundel, 1978). All of this argues in favor of using eye-tracking technology to study analogy-making strategies. There are only a small number of eye-tracking studies involving analogy-making in adults (e.g., Gordon & Moser, 2007) and even fewer in the area of the development of Thibaut, French, Missault, Gerard & Glady (2011) in which they established that children’s and adults’ analogy-making strategies differed. They showed, in the context of the A:B::C:? paradigm, that “adults looked more at A and B than at C and Target and that they start with A and B before looking at C and D, [whereas children] spent significantly more time than adults on C and the Target item (or distractors) and less on A and B.” More recently Glady, French & Thibaut (2013) focused not on looking times, but rather on full gaze-saccade paths (called scanpaths) of adults and children on three different sets of analogy problems. They developed a novel technique for analyzing these scanpaths that involved: i) modifying an algorithm developed by Jarodska, Holmqvist, & Nystrom (2010) that calculated a “distance” between any two scanpaths, ii) using a classic multidimensional scaling algorithm to represent each scanpath as a point in R 2 in such a way as to optimally preserve the distances calculated by the Jarodska et al. algorithm, and iii) using a multi-layered perceptron with a Leave-One-Out cross-validation procedure to classify and test these points according to whether they corresponded to scanpaths generated by adults or by children. By means of this technique they were able to demonstrate that there was, indeed, a clear difference in the dynamics of strategies used by children and adults in solving analogy problems of the form A:B::C:D. However, this technique revealed only that adults’ and children’s analogy-making strategies were different. The present paper is an attempt to answer a closely related question using eye-" @default.
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