A primary reason a person practices skills is to improve their ability to perform in future situations (Schmidt & Lee, 2013; Magill, 2011). In the last 20 years, the motor control literature discussed how, besides practice time, also practice quality plays a crucial role (i.e., Magill, 2011; Masters, 1993). In other words, besides extensive practice, what matters is also how a specific skill is learned.
Errorful Versus Errorless Learning
Within the motor control literature, two major learning strategies seem to emerge. On the one hand, we have a more classical and somewhat sponateous type of learning, which we can call explicit or errorful (Fitts & Posner, 1967). This involves deliberate practice and, inevitably, performance errors that trigger in the learner movement specific hypothesis-testing, in an attempt to find and store a set of explicit, declarative rules for a proficient skill execution and performance. This skill-focused hypothesis-testing process, also known as conscious processing (i.e., Masters, 1992; Maxwell, Masters, & Eves, 2003), would happen within our working memory (Baddeley, 2012), a limited-resources system which is responsible for retrieving and manipulating consciously accessible declarative knowledge so to enable our motor (and cognitive) system to control movement online. On the other hand, we have implicit errorless learning, which, as the name suggests consists in a practice schedule whereby the chance for error is reduced and the learner acquires the skill without the involvement of working-memory mediated hypothesis testing and without the creation of explicit movement rules and therefore low conscious processing (Masters et al., 2014).
What are the advantages/disadvantages of these two strategies? Errorful learning, because of its explicit focus on the skill seems to have the advantage of granting an overall faster skill acquisition. For example, Bellomo, Cooke, and Hardy (2018) showed how errorful learning during a sequence learning-task led to faster chunking, reduced conscious reprocessing, and increased cortical efficiency (higher left-temporal high alpha power) compared to errorless learning. Some theorists additionally suggest that errorful learning might also contribute to create an autonomy-supportive environment that increases confidence and self-efficacy. Errorful learning gives learners the chance to make task-relevant choices. The Optimizing Performance via Intrinsic Motivation and Attention for Learning (OPTIMAL) theory of motor learning emphasizes learner autonomy through choice possibilities. (Lee et al., 2016; Wulf, Chiviacowsky, & Cardozo, 2014; Lee et al., 2016; Sanli, Lee, et al., 2015; Chien, & Chen, 2017;Levac, Galvez, Mercado, O'Neil,2017). According to Lee et al. (2016), incorrect acts follow the mechanisms proposed by the schema theory. Guided error-based learning elucidates a student's basic schema, allowing educators to better comprehend it and employ student-centered pedagogy. Furthermore, errors in motor skills exercises may result in the storage of response information about improper motions in the brain. The database of the recall schema will be used to hold the responsive information of improper motions. To enhance the relationship with the recognition schema, reaffirmation might be done by recalling the erring experience. Wrong actions can lead to an increase in skills self-efficacy and learning effectiveness in the acquisition phase, according to the mechanics of the generalized motor program in the schema theory. However, although explicit processes would be particularly advantageous crucial early in learning, they could also backfire at later stages, once the skill has been consolitated and automatized (Masters & Maxwell, 2008). This would happen in specific scenarios, usually characterized by increased pressure performance, where stakes for errors are high and skill-failure is not an option (e.g., important competitions)(Adams, 1971). In these situations, experienced performers might try to consciously control of the execution of automatized movements, thus de-automatizing them and, in most of the cases, hindering performance. This return to conscious control is also known as “reinvestment” (Masters & Maxwell, 1992) and is the pivotal concept of Reinvestment theory (Masters, 1992; Masters & Maxwell, 2008).
And here we come to the advantages of implicit, errorless learning. In fact, the theory additionally suggests that if motor skills are learned implicitly rather than explicitly, reinvestment and therefore motor performance impairment under pressure would be less likely (since little explicit and conscious motor skill knowledge has been stored; Masters, 1993). Although several implicit acquisition of motor skills schedules have been developed throughout the years (i.e., dual-task practice; Masters, 1992; Masters, Kerr, & Weedon, 2001, removing performance or providing subliminal feedback; Maxwell et al., 2003; Masters, Maxwell, & Eves, 2009, analogy learning; Lam et al., 2009; Liao & Masters, 2001; Poolton et al., 2006; Tse, Wange, Masters, 2017; North, Warren, & Runswick, 2017)errorless learning configures itself as the most popular and implemented implicit learning strategy (Masters et al., 2004; Masters, Poolton, & Maxwell, 2008; Maxwell et al., 2001; Poolton, Masters, & Maxwell, 2007; 2005; Capio, Poolton, Sit, Eguia, et al., 2013; North et al., 2017; Capio et al., 2017; Maxwell et al.2017) and scaling of equipment (Burton & Welch, 1990; Farrow & Reid, 2010; Buszard, Farrow, Reid,& Masters, 2014). In addition to its benefits for performance under pressure, implicit learning seems to ensure a more generalized motor program, which might have additional advantages in some high pressure situations (Van Ginneken and colleagues, 2014)
On the other hand, task type can be considered a factor that influences present and past research findings and solves the challenges and conflicts and generalizations of the research literature. The nature and type of the task is an under-explored variable in this field, Mount, Parker, et al., (2007) and Levac et al., (2017) argued that more research is needed to identify the characteristics of tasks, such as task complexity, motor versus non-motor tasks, and type of task (laboratory tasks or non-laboratory tasks) in errorless and errorful approaches. To the best of our knowledge, errorless and errorful practice approaches have been addressed just in fine tasks such as golf putting, button-press task (Maxwell, Masters et al., 2001; Poolton, Zachry, 2007; Zhu, Wilson, Maxwell, & Masters, 2011, Bellomo et al., 2018) or gross-motor tasks rugby throws,respectively (Masters, Poolton & Maxwell, 2008; Gabbet & Masters, 2011).
Although most researching work performed on errorless and errorful protocols has been somewhat confirmed in indicators such as distance from the target (e.g., Maxwell et al., 2001; Poolton et al., 2005; Zhu, Poolton et al., 2011; Maxwell, Capio et al., 2016; Sanli&Lee,2014 Experiment 2) or target size (Capio, Masters, et al., 2013; Masters et al., 2008; Ong, Lohse, Sze, & Hodges,2013; Sanli&Lee,2014 Experiment 1). However, some studies report limited evidence of the efficacy of error-reduced learning in field and laboratory setting (Sanli & Lee, 2014; Ong, Lohse, & Hodges, 2015; Lee, Eliasz, Gonzalez, Alguire, Ding, Dhallwal,2016).
In contrast, Sanli and Lee (2014) in studies in two experiments showed that skill training with the gradual progress from easy -to difficult (error reduced) did not consistently induce implicit learning processes and is not consistently beneficial to performance under secondary -task load. The experiment findings did not support the predictions based on schema theory and only partially supported the predictions based on reinvestment theory.
Sanli and Lee (2014) suggested that the timing of errors with task difficulty (functional difficulty) is probably an important factor in motor learning. but they also found minimal evidence to support previous claims that error-reduced approaches cause implicit motor learning. In this regard, Lee et al. (2015) in a study investigated the role of errors in learning a laboratory task of distinct keypress sequences that varied in the amounts of advance information (i.e., choice). Although these findings support the beneficial role of error in motor learning, they also suggest that not all errors are equal in the learning process. Instead, they distinguish between factors that cause errors that have a desirable effect on learning than those that have an undesirable effect. Ong et al. (2015) revealed that also participants throwing darts at a larger target (i.e., error reduced) did not differ in performance (radial error) during practice (90 trials) or under secondary task load, compared to those who are throwing at a small target (i.e., error-strewn).
Sanli and Lee (2014) suggested that the timing of errors in relation to task difficulty is likely to be a critical factor in motor learning. We selected a fine-motor task in a laboratory setting so that we could assess performance more precisely, such as the size and variability of error. We were also particularly interested in the impact of different implicit and explicit learning paradigms on immediate and delayed retention, dual-task, and transfer tests.Therefore, there are some criticisms of these papers; specifically, that the present research is seeking to study the effect of errorless and errorful practice on learning by manipulating relative timing as an unknown issue that is an invariant feature of the generalized motor program (Schmidt, 1975), rather than by emphasizing variabilities and parametric indicators. In the present research, a fine-motor task that has been used more in the early works (Lai & Shea, 1998; Lai & Shea et al., 2001; Rahbanfard & Proteau, 2011; Apolinário-Souza, Ferreira, Oliveira, Nogueira, Pinto and Lage,2020) was employed to provide the possibility of more accurate assessment of performance, such as size and variability of errors.Thus, given the challenges and contradictions in the past literature on the efficacy of errorless and errorful practice in learning tasks, there is a partial timing (Sanli et al., 2014; Lee et al., 2015) yet unclear or inconsistent and wholly understood.
Although most previous studies search implicit learning is useful in learning motor skills. but the new line of the present study is the study of retention and immediate transfer, assessments of delayed task recall and transfer have not been studied as extensively (Poolton & Zachry, 2007). The disadvantage of not having delayed retention and transfer tests is that the condition that is beneficial to performance during acquisition may be detrimental to learning in other situations.
Recent evidence suggests that some conscious processes may be beneficial to beginners during learning, but but detrimental in the performance under pressure. Therefore, the present study seeks to fill this gap. Based on previous research (bellomo et al., 2018), we hypothesized that participants in both groups show a timing task during acquisition, but the explicit group improves more rapidly. Also, based on the reinvestment theory (masters & Maxwell, 2008), we predicted that under pressure, the de-chunking would be greater in the explicit group, while the implicit group would be immune. we expected that in explicit group under dual-task load and under pressure following practice, pressure would elicit increases in conscious processing and possibly de-chunking of the movements therfore, we expected this to be less for implicit motor learning paradigm because implicit training should limit the rules of verbal-analytic rules required for reinvestment to occur. Moreover, In line with the retention phase findings, some studies have shown that implicit learning strategies are more stable and resilient and over time than those associated to explicit learning (Masters, Poolton, & Maxwell, 2008; Poolton, Masters, & Maxwell, 2007). Schmitz et al., (2014) believe errorless learning allows for faster automation of serial response time tasks compared to errorful learning in both alzheimer’s disease healthy older subjects. This study investigated, in a controlled laboratory enviroment, the role of motor learning errors during practice, retention, and transfer using errorless and errorful practice schedules. Previous studies only have examined performance and retention conditions. no studies have examined the conditions of delayed retention and transfer. An important aspect of the present study is the study of delayed retention and transfer conditions. We expect more robust performance under dual task in the implicit learning.
Therefore, in this study, in line with the reinvestment theory and previous research, we hypothesized that practicing a task in an incremental difficulty paradigm (easy to difficult) leads to fewer errors and more stable learning of the relative timing (GMP) compared to difficult to eary / errorful and compared to control. We also expected relatively implicit learner (errorless) to report less explicit knowledge of the performance of timing task compared to explicit (declarative) learners. Moreover, we expected the amount of reported task-specific declarative knowledge to correlate with the Movement- Specific Reinvestment (MSRS) scores in the errorful group.