AbstractThe "OPTIMAL" theory of motor learning (Wulf & Lewthwaite, 2016) was recently proposed to account for, from a motivational perspective, a select set of practice conditions that enhance learning. One of which was self-controlled practice wherein exercising choice over a practice feature produces a reliable learning advantage compared to being denied this choice (i.e., yoked practice). Within the "OPTIMAL" theory, Wulf and Lewthwaite argued that self-controlled groups are "autonomy-supportive" because exercising choice satisfies our basic psychological need for autonomy, which in turn enhances information-processing, perceptions of competency, self-efficacy, and sense of agency (pp. 1393-1394). Here, we argue that the "OPTIMAL" theory is a sub-optimal explanation for self-controlled learning advantages because it cannot explain all the data, many predictions are not clearly testable, and numerous predictions are not supported by subsequent data. For instance, there is little to no evidence supporting their claim that self-controlled groups are more "autonomy-supportive" than yoked groups (e.g., Ste-Marie et al., 2013). We therefore question the "OPTIMAL" theory as a viable explanation for self-controlled learning advantages. Instead, we argue that self-controlled learning advantages arise from more effective information-processing activities associated with performance-dependent strategies (e.g., error estimation) that ultimately reduce uncertainties regarding task performance (e.g., Carter et al., 2014; Grand et al., 2015). While we contend this perspective better accounts for existing data and that key predictions are supported, it too fails to fully capture self-controlled learning advantages. We outline current issues with both explanations and propose future avenues for this area of research.
Acknowledgments: Supported by NSERC