Looking with the (computer) mouse: How to unveil problem-solving strategies in matrix reasoning without eye-tracking
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Looking with the (computer) mouse: How to unveil problem-solving strategies in matrix reasoning without eye-tracking Guillaume Rivollier 1,2 & Jean-Charles Quinton 1 & Corentin Gonthier 3 & Annique Smeding 2 Accepted: 9 September 2020 # The Psychonomic Society, Inc. 2020
Abstract Problem-solving strategies in visual reasoning tasks are often studied based on the analysis of eye movements, which yields highquality data but is costly and difficult to implement on a large scale. We devised a new graphical user interface for matrix reasoning tasks where the analysis of computer mouse movements makes it possible to investigate item exploration and, in turn, problem-solving strategies. While relying on the same active perception principles underlying eye-tracking (ET) research, this approach has the additional advantages of being user-friendly and easy to implement in real-world testing conditions, and records only voluntary decisions. A pilot study confirmed that embedding items of Raven's Advanced Progressive Matrices (APM) in the interface did not significantly alter its psychometric properties. Experiment 1 indicated that mouse-based exploration indices, when used to assess two major problem-solving strategies in the APM, are related to final performance—as has been found in past ET research. Experiment 2 suggested that constraining some features of the interface favored the adoption of the more efficient solving strategy for some participants. Overall, the findings support the relevance of the present methodology for accessing and manipulating problem-solving strategies. Keywords Active perception . Matrix reasoning . Strategy use . Graphical user interface . Computer mouse movements
Human intelligence is most often assessed via performance on reasoning tasks: performance tests wherein participants have to solve problems through inductive or deductive reasoning. Matrix-like reasoning tests are a prototypical example of a reasoning task (Carpenter, Just, & Shell, 1990), and have long been used in intelligence tests (Wechsler, 2008). In particular, Raven’s Advanced Progressive Matrices (APM; Raven & Court, 1998) are often used by investigators. This type of task requires participants to find the missing piece of a visual display among several possibilities. Each APM item comprises two parts (see Fig. 1, which also outlines the setup for the present study). The top part is a 3 × 3 matrix; patterns are
* Jean-Charles Quinton [email protected] * Annique Smeding [email protected] 1
Univ. Grenoble Alpes, CNRS, Grenoble INP, LJK, 38000 Grenoble, France
2
Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, BP 1104 LIP/PC2S, 73011 Chambéry, France
3
Université Rennes 2, LP3C EA 1285, 35000 Rennes, France
visible in eight out of nine cells, while the bottom right cell is always empty. The objective is to find the missing pattern, which obeys a variety of logical rules (Carpenter et al., 1990; Vigneau & Bors, 2008). The bottom part contains eight response alternatives, of which only one correctly com
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