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Decision making in numeracy tasks with spatially continuous scales.

Roger Ratcliff¹, Gail McKoon¹

¹The Ohio State University, United States.

Cognitive Psychology

|December 16, 2019

Summary

A new diffusion model explains decision-making on continuous scales for numeracy tasks. It accurately predicts response distributions and decision times, offering deeper insights into numerical cognition.

Keywords:

Diffusion model Distributed representations Gaussian process noise Number-line tasks Spatially continuous scale

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Area of Science:

Cognitive Science
Mathematical Psychology
Neuroscience

Background:

Decision-making on continuous scales is crucial for numeracy.
Existing models lack comprehensive explanations for response distributions and decision times.

Purpose of the Study:

To propose and validate a diffusion model for decision-making on continuous response scales in numeracy tasks.
To account for both accuracy and response time distributions.

Main Methods:

Applied a diffusion model with continuous Gaussian process noise to three numeracy tasks.
Fit the model to experimental data involving number line placement, dot array estimation, and dot counting.

Main Results:

The model successfully explains response distributions and decision times across tasks.
Provides estimates of decision acuity and reveals task-dependent representations of numerical information.

Conclusions:

The proposed diffusion model offers a robust framework for understanding numeracy.
It enables more comprehensive assessment of individual differences in numeracy skills on continuous tasks.