Self-controlled feedback is effective if it is based on the learner’s performance: a replication and extension of Chiviacowsky and Wulf (2005)

Abstract

The learning advantages of self-controlled feedback schedules compared to yoked schedules have been attributed to motivational influences and/or information processing activities with many researchers adopting the motivational perspective in recent years. Chiviacowsky and Wulf (2005) found that feedback decisions made before (Self-Before) or after a trial (Self-After) resulted in similar retention performance, but superior transfer performance resulted when the decision to receive feedback occurred after a trial. They suggested that the superior skill transfer of the Self-After group likely emerged from information processing activities such as error estimation. However, the lack of yoked groups and a measure of error estimation in their experimental design prevents conclusions being made regarding the underlying mechanisms of why self-controlled feedback schedules optimize learning. Here, we revisited Chiviacowsky and Wulf’s (2005) design to investigate the learning benefits of self-controlled feedback schedules. We replicated their Self-Before and Self-After groups, but added a Self-Both group that was able to request feedback before a trial, but could then change or stay with their original choice after the trial. Importantly, yoked groups were included for the three self-controlled groups to address the previously stated methodological limitation and error estimations were included to examine whether self-controlling feedback facilitates a more accurate error detection and correction mechanism. The Self-After and Self-Before groups demonstrated similar accuracy in physical performance and error estimation scores in retention and transfer, and both groups were significantly more accurate than the Self-Before group and their respective Yoked groups (p’s < 0.05). Further, the Self-Before group was not significantly different from their yoked counterparts (p’s > 0.05). We suggest these findings further indicate that informational factors associated with the processing of feedback for the development of one’s error detection and correction mechanism, rather than motivational processes are more critical for why self-controlled feedback schedules optimize motor learning.

Not all choices are created equal: Task-relevant choices enhance motor learning compared to task-irrelevant choices

“…On the basis of Lewthwaite et al's (2015) conclusions, no differences in perceptions of autonomy or competence would be expected between the task-relevant and task-irrelevant groups, yet both should report significantly higher perceptions of autonomy and competence than would the no-choice group. Finally, we predicted that the taskrelevant group would demonstrate significantly more accurate error-estimation abilities than either the no-choice group (consistent with Carter et al, 2014;Carter & Patterson, 2012) and the task-irrelevant group, because neither of those groups would make a choice expected to provide any taskrelated processing benefits (Lewthwaite et al, 2015).…”

“…Both groups should, however, demonstrate superior motor learning relative to the no-choice group. In contrast, if the root cause of the learning benefits of choice are predominantly informational, as Carter et al (2014) argued, then task-relevant choices should yield motor performance in retention and transfer superior to that provided by taskirrelevant choices, which would still outperform the nochoice group. On the basis of Lewthwaite et al's (2015) conclusions, no differences in perceptions of autonomy or competence would be expected between the task-relevant and task-irrelevant groups, yet both should report significantly higher perceptions of autonomy and competence than would the no-choice group.…”

“…On the one hand, some researchers have argued that having choice or control is intrinsically rewarding and satisfies the basic psychological needs of autonomy and/or competence, which in turn enhances motor learning (Chiviacowsky, 2014;Lewthwaite, Chiviacowsky, Drews, & Wulf, 2015;. On the other hand, the learning advantages have been suggested to be predominantly driven by the learner's ability to engage in performance-dependent strategies (e.g., error estimation) that serve to reduce the uncertainty regarding task performance (Carter, Carlsen, & Ste-Marie, 2014;Carter, Rathwell, & Ste-Marie, 2016;Chiviacowsky & Wulf, 2005;Grand et al, 2015;Hansen, Pfeiffer, & Patterson, 2011;Huang, Shadmehr, & Diedrichsen, 2008). These explanations are often referred to as the motivational-influences perspective and the information-processing perspective, respectively (see both Carter et al, 2014, andSanli et al, 2013).…”

“…On the other hand, the learning advantages have been suggested to be predominantly driven by the learner's ability to engage in performance-dependent strategies (e.g., error estimation) that serve to reduce the uncertainty regarding task performance (Carter, Carlsen, & Ste-Marie, 2014;Carter, Rathwell, & Ste-Marie, 2016;Chiviacowsky & Wulf, 2005;Grand et al, 2015;Hansen, Pfeiffer, & Patterson, 2011;Huang, Shadmehr, & Diedrichsen, 2008). These explanations are often referred to as the motivational-influences perspective and the information-processing perspective, respectively (see both Carter et al, 2014, andSanli et al, 2013). To date, the learning benefits of choice for motor-skill learning have predominantly been found with choices that are relevant to learning a given motor task; however, these advantages were recently extended to choices that are irrelevant to the to-be-learned task (Lewthwaite et al, 2015).…”

Contextual Interference Effect in Bandwidth and Self-Control Feedback Conditions on Relative and Absolute Timing Learning

“…stated that the perception of selfcontrol conditions can improve learning because it leads to more active involvement of the learner in the learning process. and Carter, Carlsen, and SteMarie (2014) believed that giving learners the opportunity to control a certain aspect of practice conditions led to successful trials and successful performance strategies for learners (15,39,40). This can improve error detection and reforming them between the efforts that haven't provided any feedback and finally the respond to stability increases.…”