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Keith R. Lohse, Jincheng Shen and Allan J. Kozlowski

Background: Repeated measures analysis of variance (ANOVA) is frequently used to model longitudinal data but does not appropriately account for within-person correlations over time, does not explicitly model time, and cannot flexibly handle missing data. In contrast, mixed-effects regression addresses these limitations. In this commentary, we compare these two methods using openly available tools. Methods: We emulated a real developmental study of elite skiers, tracking national rankings from 2011 to 2018. We constructed unconditional models of time (establishing the “pattern” of change) and conditional models of time (identifying factors that affect change over time), and contrasted these models against comparable repeated measures ANOVAs. Results: Mixed-effects regression allowed for linear and non-linear modeling of the skiers’ longitudinal trajectories despite missing data. Missing data is still a concern in mixed-effects regression models, but in the present dataset missingness could be accounted for by skiers’ ages, satisfying the missing at random assumption. Discussion: Although ANOVA and mixed-effects regression are both suitable for time-series data, their applications differ. ANOVA will be most parsimonious when the research question focuses on group-level mean differences at arbitrary time points. However, mixed-effects regression is more suitable where time is inherently important to the outcome, and where individual differences are of interest.

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Mariane F.B. Bacelar, Keith R. Lohse and Matthew W. Miller

It is unknown whether rewards improve the capability to select appropriate targets for one’s movement (action selection) and/or the movement itself (action execution). Thus, we devised an experimental task wherein participants categorized a complex visual stimulus to determine toward which one of two targets to execute an action (putt a golf ball) on each trial under one of three conditions: reward, punishment, or neutral. After practicing the task under their assigned condition, participants performed an immediate, 24-hr, and 7-day post-test. Results revealed participants putted to the correct target more frequently during the post-tests than the first practice block, and putted more accurately during the post-tests than a pretest. However, the condition in which participants practiced did not moderate post-test performance (for either task component). Additionally, motivation scores explained action selection and action execution for the immediate post-test performance but not long-term retention, suggesting that motivation might be related to immediate performance, but not long-term learning. Further, the present task may be useful for researchers studying action selection and execution, since the task yielded learning effects that could be moderated by factors of interest.

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Marcos Daou, Taylor L. Buchanan, Kyle R. Lindsey, Keith R. Lohse and Matthew W. Miller

There is some evidence that people learn academic (declarative) information better when studying with the expectation of having to teach, but this has not been demonstrated for perceptual-motor skills, which also rely on declarative information but more heavily on procedural knowledge. To address this possibility, participants studied golf-putting instructions and practiced putting with the expectation of having to teach another participant how to putt or the expectation of being tested on their putting. One day later, learning was assessed by testing all participants on their golf putting. Results revealed that expecting to teach enhanced learning, even after controlling for the amount of studying and practicing. Therefore, we have presented the first findings that expecting to teach enhances motor learning. Taking these findings together with similar studies focusing on declarative information, we suggest that expecting to teach yields a general learning benefit to different types of skills.

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Amber M. Leiker, Anupriya Pathania, Matthew W. Miller and Keith R. Lohse

Considerable research has been devoted to understanding how intrinsic motivation can augment the learning of motor skills. Many manipulations targeting intrinsic motivation have led to improved learning, but the mechanisms underlying this effect are not known. Replicating a previous study, we manipulated intrinsic motivation by giving one group self-control over the difficulty of practice, while a control group was yoked to that schedule. We collected measures of intrinsic motivation, engagement, and physiological measures related to dopamine (spontaneous eye-blink rate; sEBR) and approach motivation (frontal alpha asymmetry; FAS) to understand mechanisms underlying learning effects. Although the effect of self-control was not significant in the current experiment, the overall result was statistically significant when combined with the results of our previous study. Overall, there is evidence for a benefit of self-control during practice, but the true effect-size is smaller than initially estimated. Furthermore, even though self-control led to increased intrinsic motivation in the current experiment, individual differences in motivation were not correlated with learning. Similarly, neither sEBR nor FAS were related to learning. Taking a cumulative view, these data suggest that self-control of practice is beneficial to both learning and motivation, but increased motivation does not appear to directly cause improved learning.

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Jence A. Rhoads, Marcos Daou, Keith R. Lohse and Matthew W. Miller

Expecting to teach and (actually) teaching has been shown to enhance learning academic information, possibly due to increased motivation and engagement. Recently, expecting to teach has been shown to augment motor learning. The present study investigated whether expecting to teach and teaching enhances motor learning, and whether motivation or engagement could explain this effect. Two groups studied/practiced golf putting with the expectation of teaching the skill via video demonstration at the end of practice, while the other two groups studied/practiced without this expectation. Following studying/practice, half of the participants who expected to teach performed a 2-min video demonstration of golf putting (Expect/Teach group). The other participants who expected to teach simply practiced for an additional 2-min (Expect/No Teach group). Similarly, half of the participants who did not expect to teach performed a 2-min video demonstration (No Expect/Teach group), while the other half engaged in additional practice (No Expect/No Teach group). Next, all participants self-reported their motivation and engagement. One day later participants were tested on their putting skills. Results did not reveal an effect of expecting to teach, teaching, or an interaction between these variables. However, exploratory analyses revealed motivation and engagement predicted motor learning, irrespective of group.

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Kirk F. Grand, Marcos Daou, Keith R. Lohse and Matthew W. Miller

The present study investigated whether motivation and augmented feedback processing explain the effect of an incidental choice on motor learning, and examined whether motivation and feedback processing generally predict learning. Accordingly, participants were assigned to one of two groups, choice or yoked, then asked to practice a nondominant arm beanbag toss. The choice group was allowed to choose the color of the beanbag with which they made the toss, whereas the yoked group was not. Motor learning was determined by delayed-posttest accuracy and precision. Motivation and augmented feedback processing were indexed via the Intrinsic Motivation Inventory and electroencephalography, respectively. We predicted the choice group would exhibit greater motor learning, motivation, and augmented feedback processing, and that the latter two variables would predict learning. Results showed that an incidental choice failed to enhance motor learning, motivation, or augmented feedback processing. In addition, neither motivation nor augmented feedback processing predicted motor learning. However, motivation and augmented feedback processing were correlated, with both factors predicting changes in practice performance. Thus, results suggest the effect of incidental choices on motor learning may be tenuous, and indicate motivation and augmented feedback processing may be more closely linked to changes in practice performance than motor learning.