Abstract

We describe a computational multi-attribute decision model that predicts the decision aspect of sequential multitasking. We investigate how people choose to switch tasks or continue performing an ongoing task when they are in overload conditions where concurrent performance of tasks is impossible. The model is based on a meta-analytic integration of 31 experiments from the literature on applied task switching. Consistent trends from the meta-analysis, to avoid switching, and to switch to tasks lower difficulty, along with greater salience, priority and interest are used to set polarity parameters in the mathematical model.

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