As the workplace becomes more complex there is an increasing need to further our understanding of the adaptive process that occurs in order to maintain the effectiveness of individuals facing changing circumstances. This study is an extension of previous work in the performance adaptation literature investigating the effect of training inductions and self-regulatory variables on individual performance trajectories after an adaptive change in a lab based computer simulation. Bivariate latent difference score models were used for analyses and revealed that trainings that encouraged errors were most beneficial for the adaptation of individuals. Furthermore, when individuals were not informed to avoid errors but were given an opportunity to learn the task through exploration, they adapted better than if they were given step-by-step instructions. With regard to the self-regulatory processes, individuals who were able to identify the origin of the change in the task and sought feedback and information that aligned with that change required less of that information over time. When motivation was high, performance was increased; however, less effort was needed to have increased performance when individuals devoted effort to the aspects of the task that changed versus simply increasing their amount of effort. Although this study takes the next step of investigating the self-regulatory processes during adaptation, future research should investigate how these processes, taken together, create a cycle of self-regulation that influences the adaptation of individuals.
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