Variable training does not lead to better motor learning compared to repetitive training in children with and without DCD when exposed to active video games
Introduction
Despite the wealth of research on differences in motor behavior and its underlying processes between typically developing (TD) children and those with Developmental Coordination Disorder (DCD), little is known about practice conditions that facilitate efficient motor skill training, and about factors that influence the course of motor learning (Wilson, Ruddock, Smits-Engelsman, Polatajko, & Blank, 2013). There is no doubt that children with DCD are able to learn new motor skills or improve upon existing ones when given adequate training (Miyahara, Hillier, Pridham, Nakagawa, & Miyahara, 2014; Zwicker, Missiuna, Harris, & Boyd, 2012). However, investigations of how to effectively manipulate practice conditions to create optimal learning experience are still lacking.
Motor learning refers to the processes that allow individuals to acquire new motor skills and to adjust their movements to changes of the physics of the body and the world (Kroemer, Burrasch, & Hellrung, 2016). Though there is a general consensus that motor learning leads to improvement in motor skills beyond baseline levels, these improvements are not seen as indication of learning (Shmuelof, Krakauer, & Mazzoni, 2012). Rather, improvements observed in retention of acquired skills over time and transfer (ability to apply acquired skills in novel situations) are used as key determinants of motor learning in human subjects (Shea & Morgan, 1979). Also, motor learning is described as a set of internal unobservable processes that occur with practice or experience resulting in permanent changes in movement capacity (Schmidt & Lee, 2011). Acquisition of skilled movements is influenced by various factors such as attention focus, type and frequency of feedback, amount of practice and practice schedules (Wulf, Shea, & Lewthwaite, 2010).
Practice schedules refer to the ways practice and/or training sessions are designed and structured to optimize learning outcomes (Muratori, Lamberg, Quinn, & Duff, 2013; Vera, 2008). Generally, two forms of practice schedules are described in the motor learning literature: repetitive (or constant) and variable practice (Shea, Kohl, & Indermill, 1990). Repetitive practice is the continuous repetition of one skill during an episode of training, whereas variable practice involves the execution of a wider variation of skills (Lage et al., 2015). It is now known that training the task to be learned repetitively (constant practice) leads to improved practice performance but results in poor retention and transfer (Battig, 1966, Shea and Morgan, 1979). The advantage of repetitive practice may be that performing many repetitions leads to automatization of that skill, and enables temporal and spatial adaptations of this specific skill (For example, the skill improves in speed, accuracy, stability and fluency). Nonetheless, variable practice leads to increased retention and transfer (Lee and Magill, 1983, Muratori et al., 2013, Schmidt and Lee, 1988, Shea and Morgan, 1979) and is widely regarded as superior to repetitive practice in terms of enhancing skill learning.
The idea that motor learning benefits more from practicing tasks in a variable rather than repetitive practice context is known as contextual interference (CI) effect (Feghhi, Abdoli, & Valizadeh, 2011; Magill, 2004; Shea & Kohl, 1990). From a neurocognitive perspective, sensorimotor learning involves learning new mappings between motor and sensory variables. Such mappings are termed internal models, as they represent features of the body and the environment. When we learn new movements, we must be able to link them to appropriate contextual cues such as objects, tasks or environments (Wolpert, Diedrichsen, & Flanagan, 2011). For example, expert video game players develop an extraordinary ability to extract information and spread their attention over a wide spatial frame without any apparent decrease in performance (Green & Bavelier, 2003).
One of the prominent hypothesis for the poor motor control in DCD concerns deficit in the internal modeling of movements (Wilson et al., 2013). According to this hypothesis, children with DCD have significant limitations in their ability to accurately generate and utilize internal models of motor planning and control. Since learning is strongly determined by the neural representations and influences how learning generalizes to novel situations, deficits in internal representations will not only hamper skill acquisition but also transfer of motor learning. As an example; when playing a new or untrained computer game on a balance board, after playing many other active computer games during 5 weeks, the relevant inputs stay comparable (the moving and stationary images on the screen) and the task relevant output will be similar, namely rapid weight shifts. It is hypothesized that by playing many different games (variable training), the child extracts general rules for how to control the coveting parameters for different games (Braun, Aertsen, Wolpert, & Mehring, 2009). What differs between the various computer games are the parameters of inputs and outputs, such as the path through which the children have to steer round the obstacles that have to be avoided, and the amount and timing of the weight shifts. Given these comparable task constraints, we can expect transfer of learning, which can be evaluated by the more rapid learning of other comparable tasks. On the other hand, if the child plays one game over and over again, it will become better at that game. However this creates relatively less contextual interference during training because it involves executing the same motor task repeatedly. The child playing many different but comparable games, may also have improved performance on the games played, but will likewise have learned the basic structure of a balance steered computer game and transfer. By playing multiple motor tasks, contextual interference (CI) effect is assumed to create relatively high interference throughout practice because of the rapid changes in task demands from game to game (Shea & Morgan, 1979). In short, it is expected that high levels of CI (variable practice) would result in poorer performance but increased retention and transfer compared to low levels of CI. This is because during acquisition stage of learning, variable practice creates opportunities for more effortful cognitive processing (Lin, Sullivan, Wu, Kantak, & Winstein, 2007) and structural learning (Braun et al., 2009). Previous motor learning research in children with DCD focused on a Serial Reaction Time paradigm (Gheysen, Van Waelvelde, & Fias, 2011; Lejeune, Catale, Willems, & Meulemans, 2013; Wilson, Maruff, & Lum, 2003). To date, no study has examined the impact of practice schedule manipulation in children with DCD. Recent studies have introduced active video games (exergames) in children with DCD and several other populations (Bonnechère, Jansen, Omelina, & Van Sint, 2016; Deutsch, Borbely, Filler, Huhn, & Guarrera-Bowlby, 2008; Hammond, Jones, Hill, Green, & Male, 2014; Jelsma, Ferguson, Smits-Engelsman, & Geuze, 2015; Lohse, Hilderman, Cheung, Tatla, & Van der Loos, 2014; Mendes et al., 2012; Smits-Engelsman et al., 2013), yet the extent to which practice schedules affect learning during gameplay is unknown. Given that balance problems are common in children with DCD (Cherng, Hsu, Chen, & Chen, 2007; Deconinck, Savelsbergh, De Clercq, & Lenoir, 2010; Geuze, 2003; Grove & Lazarus, 2007), we investigated the influence of practice schedules on motor learning using selected balance games on a commercially available active video game console.
In this study, we designed an experiment to determine what practice schedule would work best in enhancing perceptual-motor learning in children. Specifically, we evaluated the effect of two practice schedules on motor learning and transfer in children with DCD and their typically developing peers. We hypothesized that improvement in game performance score, which encompasses speed and accuracy, would be less when children play 10 different games on the Wii (Variable practice schedule) than when they play only one game repetitively (Repetitive practice schedule). Next, it was expected that the variable practice schedule would enhance learning and facilitate transfer to untrained comparable tasks more effectively than repetitive practice. In light of the aforementioned considerations, the following specific questions were addressed:
- 1)
Are there differences in improvement and retention in game performance between repetitive and variable practice schedule during 5 weeks of training?
- 2)
Are there differences in near transfer to a comparable virtual static balance task between repetitive and variable practice schedule during 5 weeks of training?
- 3)
Are there differences in performance on the Criterion test between repetitive and variable practice schedule after 5 weeks of training?
- 4)
Do children learn the criterion test faster after they have played many different Wii games for 5 weeks (Variable practice schedule)?
- 5)
Is the level of motor competence (TD vs. DCD) a mediating factor in the rate of learning and the amount of transfer?
Section snippets
Research design
A stratified randomized pre-post single blinded design was used to evaluate changes in performance during and after 10 training sessions (two times per week for 5weeks) using the Nintendo® Wii Fit games in children with and without DCD.
Pre- and post-test for both groups involved the same Criterion test (see Fig. 1). In this experiment, the Criterion test was followed by practicing either the ski slalom game (same game as used in the Criterion test) repetitively, or variations of 10 other
Group comparability
Parents of one TD child assigned to the Repetitive practice schedule gave permission for the pretest but did not consent for the training and so that child could not participate in the training. The Repetitive game group therefore consisted of 55 children whereas the Variable game group had 56 children. For one child, a classification error was made (two children with the same first name got the same code which lead to randomization mistake) in the pre-selection process. We left this child with
Discussion
In this study, we sought to ascertain if variable or repetitive practice schedule enhances sensorimotor learning best. The findings were based on changes brought about by participating in a 5-week active video games using two-practice schedules, either playing the same game over and over again, or engaging in a free choice of 10 different games. The data gave the following answers to our research questions:
- 1.
There is no difference in improvement in the mean standardized game scores in Repetitive
Conclusion
Our findings suggest that playing active video games enhances sensorimotor learning and yields superior performance. Effect of active video gaming is large, whether children follow repetitive or variable practice schedule. There are clear indications of transfer after active computer training to tasks that share common elements. Variable practice schedule does not enhance the transfer effect. Although we are replicating previous findings that children with DCD perform poorer on exergames, the
Conflicts of interest
The authors have no conflict of interests to declare.
Acknowledgements
The authors would like to thank the students for assisting with the data collection, the teachers of the participating schools for their support, as well as all the children and their families.
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