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  • 1Manchester Business School, University of Manchester, Manchester, United Kingdom. stephen.payne@manchester.ac.uk

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Summary

Participants frequently switched between word-generation tasks to maximize productivity. This task-switching behavior, observed in Scrabble and word-search puzzles, balances continuous rewards with subgoal completion for optimal performance.

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Area of Science:

  • Cognitive Psychology
  • Decision Making
  • Human-Computer Interaction

Background:

  • Individuals often need to allocate time and effort between multiple concurrent tasks.
  • Understanding the dynamics of task switching is crucial for optimizing performance and productivity.
  • Previous research has explored factors influencing switching behavior, but a unified model is lacking.

Purpose of the Study:

  • To investigate the decision-making process underlying task switching in a word-generation context.
  • To identify the key factors influencing participants' decisions to switch between tasks.
  • To develop and test a model that explains task-switching behavior based on dual orientations.

Main Methods:

  • Participants engaged in two word-generation tasks (Scrabble, word-search puzzles) with varying productivity.
  • Time allocation and "giving-up times" between task switches were systematically recorded.
  • Switch decisions were analyzed in relation to task productivity, ease, and potential gain.

Main Results:

  • Frequent task switching was observed, allowing participants to allocate more time to more productive tasks.
  • Switching behavior was influenced by a continuous rate of return (information foraging) and subgoal completion.
  • Giving-up times were longer in less productive tasks, yet switches still occurred to optimize overall output.
  • Switch decisions were largely unaffected by the ease of the competing task or explicit gain information.

Conclusions:

  • Task switching is a strategic behavior driven by a dual orientation: sensitivity to continuous rewards and completion of subgoals.
  • An information-foraging approach, combined with subgoal completion, effectively predicts task-switching patterns.
  • The findings provide a robust model for understanding adaptive decision-making in dynamic task environments.