Task-ordering across domains: Hard-first preferences emerge through learning

Many everyday goals require people to complete multiple tasks of varying difficulty, yet how they decide on the order of executing these tasks remains unclear. Using a novel, pre-registered procedure across four task domains (perceptual decision-making, arithmetic problem-solving, visuomotor control, and gambling), we investigated choices between starting with easy versus hard task components when both components must be successfully completed to obtain a reward. Participants (N = 230) showed no easy-first preference. Instead, they preferred doing the hard part first in two of the four tasks (gambling and visuomotor control). Although task order preferences showed some stability across task domains, time-on-task analyses revealed systematic changes with experience: participants developed increasingly more hard-first preferences both within tasks and across the experiment. Computational modeling shows that order choices are driven by learning at both the task component and task sequence level, suggesting that people combine local effort-related considerations and more global assessments of strategy effectiveness when deciding on the order of completing tasks.