The influence of rewards on (sub-)optimal interleaving

Area of Science:

• Cognitive Psychology
• Human-Computer Interaction
• Behavioral Economics

Background:

• Individual differences in task interleaving efficiency are known.
• The impact of task reward structures on expected interleaving efficiency is under-explored.
• Understanding optimal strategies for dual-task performance is crucial.

Purpose of the Study:

• To investigate how individual task rewards influence the a priori ease of efficient dual-task interleaving.
• To determine if people actually interleave tasks efficiently based on reward structures.
• To identify and model different dual-task interleaving scenarios based on reward rates.

Main Methods:

• Developed a simulation model to explore dual-task interleaving scenarios based on task rewards.
• Identified three distinct scenarios: easy, difficult, and constrained, based on reward structures.
• Conducted three empirical studies where participants performed interleaved tasks under these scenarios.

Main Results:

• Simulation results predicted varying degrees of optimization opportunity and strategy variation across scenarios.
• Empirical findings aligned with simulation predictions, showing participants' interleaving strategies matched theoretical patterns.
• Easy scenarios allowed strategy variation, difficult scenarios offered little optimization, and constrained scenarios guided optimal strategies.

Conclusions:

• Task reward structures significantly predict the feasibility and nature of efficient dual-task interleaving.
• Constrained scenarios are most effective for assessing general human capability in optimizing interleaving strategies.
• Findings have implications for designing tasks and understanding human performance in complex, multi-task environments.