<p>While the domain of cognitive training is extremely broad, encompassing many different training paradigms and training targets, essentially all paradigms require that participants persist in engaging with a specified training task (or set of tasks) over a long period of time (e.g., tens or even hundreds of hours spaced over weeks or months). As such, in the real world, individuals must sustain motivation to persist in the training of their own volition. Interestingly though, most of the basic science work on cognitive training bypasses the issue of a potential lack of persistence by directly compensating participation (e.g., paying participants). Here we examine the persistence issue through the lens of expectancy-value theory. Participants were provided falsified feedback indicative of different types of performance (e.g., being good at a task from the outset; being able to quickly learn a task) and the impact of those manipulations on persistence behavior was assessed. We found that feedback indicative of improvement was related to longer-term sustained effort, while feedback indicating “good” performance (but no improvement through time) was not. Furthermore, we provide evidence that participants may use local calculations in assessing their current and future improvement, which presents challenges for providing feedback that is both accurate and motivating in the context of cognitive training paradigms.</p>

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Applications of Expectancy-Value Theory in Promoting Motivated Behavior in Cognitive Training

  • Lauren E. Anthony,
  • Aaron Cochrane,
  • Victoria Klaas,
  • Cameron A. Hecht,
  • C. Shawn Green

摘要

While the domain of cognitive training is extremely broad, encompassing many different training paradigms and training targets, essentially all paradigms require that participants persist in engaging with a specified training task (or set of tasks) over a long period of time (e.g., tens or even hundreds of hours spaced over weeks or months). As such, in the real world, individuals must sustain motivation to persist in the training of their own volition. Interestingly though, most of the basic science work on cognitive training bypasses the issue of a potential lack of persistence by directly compensating participation (e.g., paying participants). Here we examine the persistence issue through the lens of expectancy-value theory. Participants were provided falsified feedback indicative of different types of performance (e.g., being good at a task from the outset; being able to quickly learn a task) and the impact of those manipulations on persistence behavior was assessed. We found that feedback indicative of improvement was related to longer-term sustained effort, while feedback indicating “good” performance (but no improvement through time) was not. Furthermore, we provide evidence that participants may use local calculations in assessing their current and future improvement, which presents challenges for providing feedback that is both accurate and motivating in the context of cognitive training paradigms.