Written by Peter Joffe
“Learning is finding out what you already know. Doing is demonstrating that you know it. Teaching is reminding others that they know just as well as you. You are all learners, doers, teachers.”
Richard Bach
Recently, I was observing an Under 11 boys football training session, which was led by a Level 2 FA coach. He was trying to explain a defender’s body position when an attacker moves towards him. He stopped the session, picked up one unfortunate boy and, for no less than 15 minutes, tortured him with the angles and limbs alignments. All this time, the other kids were static spectators.
As I watched, I thought of the rule an old professor of the Training Methodology had taught me 30 years prior: “Don’t speak too much during your training session. Create an exercise that will do the talking for you.” In 2010, during my study in the University of Exeter I have discovered that “unconscious learning” for some years is debated in Psychology. Then, for the first time, I have learned about Implicit Learning.
What is Implicit Learning?
Numerous studies have proved that humans can acquire information unintentionally and unconsciously. For example, the Serial Reaction Task paradigm was used for exploring the learning processes. In this paradigm, participants learned to react to stimuli, unaware that there was some logical structure in the sequence of stimuli presentation. The level of unconscious learning was checked by the unexpected changing of this sequence upon another sequence. Reaction times had increased.
That could be evidence as to the participant’s “knowledge” of the previous sequence (even though they were unable to express it), and that facilitated their reactions. In another example, researchers asked participants to study letter strings generated from some grammar rules and then tested their ability to judge whether or not new strings conformed to the same rules. Participants had performed with the “better than chance” accuracy, though were unable to report the rules.
These and other experiments (see Shanks, 2005 for a review) supported the basis of what has since developed into the theory of “Implicit Learning.” This means of the acquisition of new skills may be beneficial in many areas including Sport.
Implicit Learning in sport training
There are a few training methods in Sport that can actually facilitate acquisition without significant conscious efforts.
Firstly, the coach can create conditions that simply not allow the student to make incorrect movements. For example, when one boxing coach was not happy with the too “narrow” stance of his pupils (their legs were positioned on a straight line with an opponent, instead of being kept diagonally, making them vulnerable to the side step maneuvers and, in addition, their back hand was obstructed), I made a suggestion. During the usual boxing drills, I advised him, make boxers move along a low and long gymnastic bench 30 cm wide, while positioning their feet on a floor in opposite sides of the bench. In these conditions, they were forced to keep their feet at least 30 cm wide, all the time, even if they were too busy with the drills to think about stance. Soon, having a wider position became natural.
A second method is including “analogy” rather than “declarative” instructions during the acquisition of new skills. Analogy, or metaphoric description of the action, connects with a visual image, to help the learner “feel” a movement. In contrast, the declarative method provides explicit verbal instructions about biomechanical aspects (Liao & Masters, 2001).
For example, when players learn a table tennis shot, they can be advised to move the bat “as if it travelling up the side of a mountain,” or can be given a sequence step by step instructions such as: 1.Keep your feet a little wider than shoulder width apart. 2. Position your feet behind the table with the right foot farthest from the table…6. Keep your bat face at a vertical angle…and so on (R. S. Masters, Poolton, Maxwell, & Raab, 2008). The analogy method is not completely implicit, since students are actually “aware” about what they are learning. At the same time however, their knowledge about technique is not explicit, and they usually cannot report any biomechanical features of the movement. It worthwhile to note that metaphoric learning is widely used in the Oriental Martial Art practice, where it is, arguably, the main method.
Introducing a second, “distractive” task is one strategy that is used to divert attention from the task being studied, thus make learning unconscious. An example of this may be solving simple arithmetic tasks while simultaneously learning a tennis shot (or golfing putt, etc.). As will be demonstrated further, the influence of dual-task intervention on performance is, in my opinion, far from obvious.
There are some other interesting methods to create implicit and “semi-implicit” conditions in training. The interested reader can find a detailed analysis in R.C. Jackson and Farrow’s paper (Jackson & Farrow, 2005).
Benefits
When we consider the benefits of one training concept in comparison to another, we are interested in a few things:
1. Will new skills be learned better?
2. Is it faster?
3. Is it simpler and more enjoyable? This is especially important when the learners are children.
4. Will the learned skills be more stable in the real competitions?
To answer the first question, we may take into account that, even in the early stages, implicit learners can acquire some characteristics of a movement that are otherwise inherent to expert performers (R. S. Masters, et al., 2008). Examples may be speed, amplitude and fluency. When these characteristics are genuinely presented in an athlete’s technique from the very beginning, it is, in my opinion, highly important for his/her future development. Their explicit counterparts probably cannot gain these qualities early, because their actions follow step-by-step instructions. Thus, they may separate smooth movement into the parts and slow down its execution.
The answer to a second question about the advantage in acquisition’s speed for the implicit learners probably will be negative. I have not found such benefit in the researches in table tennis (Liao & Masters, 2001; R. S. Masters, et al., 2008),(Poolton, Masters, & Maxwell, 2006), and in golf (Mullen, Hardy, & Oldham, 2007). Moreover, if the second task was used for facilitating the implicit process, then acquisition was slower, probably as a consequence of the additional mental load, which could distract learning process (Hardy, Mullen, & Jones, 1996). This detrimental effect may, in fact, last significantly long and can put into question a reasonability use of the second task at the initial stages of the skill’s acquisition (Liao & Masters, 2001).
The study, which found that explicit learning is dependent on IQ, whereas implicit is not, can be considered as a proof that the latter is more simple (Maybery, Taylor, & O’Brien-Malone, 1995). Though, in this case, the task was non-related to the sport. Another interesting area of research compared the acquisition of motor skills for children with Down’s syndrome to healthy controls (Vinter & Detable, 2008). It was found that in implicit conditions, the Down’s syndrome group was equal to the controls, whereas explicit learning was less beneficial.
These findings also may be interpreted as the advantage of the implicit method in its simplicity. Although these studies cannot be considered as a direct proof, my personal coaching experience has further supported my opinion that implicit method in sport training is more accessible and enjoyable, especially for children.
Implicit Learning and stress
Stress in Sport can be provoked by different factors. This may include social pressure, determined by the level of competitions, extreme physical load and time-constrained conditions. Very often at high-level competitions all of these factors come together. Since high stress and anxiety are typical traits in these peak moments, understanding the mechanism of their influence and thus possibility to manipulate them is crucial for success.
Though anxiety can significantly influence the athlete’s performance, it does not necessarily mean that the result deteriorates. Sportsman can allocate additional physical and mental resources to a demanding task to support the level of performance. Nevertheless, this allocation can make the ratio between efforts and results less efficient (Wilson, 2008). In situations which demand a huge amount of our Working Memory’s capacities, spending these resources for stress coping may lead to a shortage in these capacities for the main task and thus can impair the performance.
The negative influences of stress can realise itself in several ways. One example of particular interest in connection to learning is “re-investment,” when a performer facing competition in a stress situation begins to direct his/her attention to the skills and movements which should already be automatic, and do not need conscious control. This re-investment may cause the athlete to make sudden mistakes in technical actions, which are relatively simple and were performed, without error, a thousand times before (R. Masters & Maxwell, 2008).
There is a widespread notion in contemporary Sport Psychology that explicitly learned skills are more vulnerable in stress conditions, probably due to re-investment. Explicit learning can promote re-investment because the athlete keeps in his/her memory a detailed, step-by-step instruction about movement execution, often in the form of verbal guidance. Under the stress, this athlete may unwillingly start to follow this guidance and divide smooth and fluent execution into separate blocks that would be detrimental for expert performance.
Additionally, such excessive attention to the technical details can draw limited Working Memory resources from other aspects of performance (e.g. tactical awareness). Interestingly, Smeeton with colleagues compared the effectiveness of more explicit and less explicit learning techniques in young intermediate tennis players (Smeeton, Williams, Hodges, & Ward, 2005). They found a negative correlation between the amount of conscious knowledge about the technique and speed-accuracy of the performance.
As opposed to explicit, implicit learners have “nothing” to re-invest. They have no detailed knowledge about their technique although they can perform it perfectly. Thus, under the pressure, their attention remains undistracted by the revising of already learned skills.
Creativity and Implicit Learning
One of the most interesting and widely unexplored aspects of Implicit Learning is its connection with such traits of performance as anticipation and decision making. It has been proven that expert performers are better in these areas compared to less experienced athletes. They have an advantage in the speed and accuracy of their reactions, which is based on the ability earlier and more precisely to detect related visual cues. Moreover, experts are superior in the game’s patterns recognition. As a result, they may make better predictions of the opponent’s actions, even before some significant preparatory movements occur (Abernethy, Gill, Parks, & Packer, 2001).
It is obvious that more experienced and higher level athletes make better tactical decisions as well. What is not clear is how and to what extent the style of training (explicit or implicit) may influence the outcome in decisions made during real situations. Moreover, I tend to agree with Raab and Jonson that the learning process cannot be described by a dichotomy of implicit vs. explicit. Instead, it exists on a graded continuum, when, most often, learning methods integrate both approaches and can be described as “more/less implicit/explicit”. In the same paper, the authors pointed out that decision making itself has different stages, which can differ on the implicit-explicit scale and may be differently influenced by training (Raab & Johnson).
Implicit Learning more likely promotes intuitive decisions, because one cannot think about what he/she does not know. In contrast, explicit knowledge promotes deliberate decisions, because it is difficult not to think about that which you have a detailed knowledge. In theory, intuitive decisions will be superior in speed because they “bypass” high-level brain systems responsible for conscious actions.
However, explicitly learned action may become automated as well. For example, in my own experiment with the computer-based 4-choice visual reaction programme, participants were required to push a keyboard button that corresponded to a particular geometrical figure (circle, triangle, square and pentagon). Simple explicit rules, which aimed to help memorise figures-buttons combination, were suggested. Participants underwent 13 training sessions and took part in competition. After a one year break during which they had no access to the programme, I managed to repeat this test with some of them. In this case I had changed the combination and did not give training. Participants struggled with the new combination and continued to follow the old one, even though they had not trained in it for more than a year. This effect increased when the time allowed for reaction decreased.
This situation demonstrate that decision making was automated, though it had been learned explicitly. Kibele proposes that, during practice, the subject, through the “internal code,” establishes connections between particular stimuli and the correspondent responses, integrating these into the single stimulus-response reaction. After a sufficient amount of practice, just the presentation of the stimulus itself is enough to activate the motor response, without the participation of high-level brain structures (Kibele, 2006). In the same paper he argued, “rapid motor reactions are primed by the perception of non-consciously represented movement features embedded in the movement sequences of sports patterns.” So, what if during explicit learning, these “movement features” have been studied consciously? Some authors suggest that it would be beneficial for decision making, especially with the increasing complexity (Raab & Johnson).
It is difficult, if at all possible, to conduct a study that replicates long and complicated learning process. Therefore, exact, scientifically-based advice about how to teach creativity would be impossible. My personal opinion tends to be in favor of the implicit methods while learning less complicated situations, after that, based on these already “intuitively trained” patterns, more complicated situations can be learned explicitly.
Conclusion: Make it as implicit as possible.
In writing this article, I am not claiming the expertise and knowledge of experts in this field. Definitely, there are no revelations presented. However, I hoped to touch the important aspects in coaching practise (especially for children’s training), that greatly influence the future athlete’s development. It’s possible that not all coaches (even at a good level) or parents are aware about this problem. Hopefully, they will find information offered here to be useful.
In my personal view, there are strong evidences that technical skills, acquired implicitly, are more fluent, coherent and stress-resistant. Moreover, implicit methods are simpler in acquisition and more enjoyable. That is critically important when training children. When creativity is considered, I think that implicitly developed building “blocks” of intuitive knowledge helps to form more complicated tactical thinking.
It is clear that a long-term training process, as well as acquisition of the particular skills, cannot be purely explicit/implicit. It includes both conscious and unconscious components. Nevertheless, I tend to advise to keep learning as implicit as possible.
Without a doubt, the creation of implicit exercise is much more difficult than simply “enforcing” knowledge through the verbal instructions. It demands remarkable creativity, coaching intuition and unusual approaches. However, it will be rewarded with the emotionally, technically, physically and mentally efficient training sessions that ultimately lead to developing a world-class athlete.
References
Abernethy, B., Gill, D. P., Parks, S. L., & Packer, S. T. (2001). Expertise and the perception of kinematic and situational probability information. Perception, 30(2), 233-252.
Hardy, L., Mullen, R., & Jones, G. (1996). Knowledge and conscious control of motor actions under stress. Br J Psychol, 87 ( Pt 4), 621-636.
Jackson, R. C., & Farrow, D. (2005). Implicit perceptual training: how, when, and why? Hum Mov Sci, 24(3), 308-325.
Kibele, A. (2006). Non-consciously controlled decision making for fast motor reactions in sports–A priming approach for motor responses to non-consciously perceived movement features. Psychology of Sport and Exercise, 7(6), 591-610. doi: 10.1016/j.psychsport.2006.05.001
Liao, C. M., & Masters, R. S. (2001). Analogy learning: a means to implicit motor learning. J Sports Sci, 19(5), 307-319.
Masters, R., & Maxwell, J. (2008). The theory of reinvestment. International Review of Sport and Exercise Psychology, 1(2), 160 – 183.
Masters, R. S., Poolton, J. M., Maxwell, J. P., & Raab, M. (2008). Implicit motor learning and complex decision making in time-constrained environments. J Mot Behav, 40(1), 71-79.
Maybery, M., Taylor, M., & O’Brien-Malone, A. (1995). Implicit learning: Sensitive to age but not IQ. Australian Journal of Psychology, 47(1), 8-17. doi: 10.1080/00049539508258763
Mullen, R., Hardy, L., & Oldham, A. (2007). Implicit and explicit control of motor actions: revisiting some early evidence. Br J Psychol, 98(Pt 1), 141-156.
Poolton, J. M., Masters, R. S. W., & Maxwell, J. P. (2006). The influence of analogy learning on decision-making in table tennis: Evidence from behavioural data. Psychology of Sport and Exercise, 7(6), 677-688. doi: DOI: 10.1016/j.psychsport.2006.03.005
Raab, M., & Johnson, J. G. Implicit learning as a means to intuitive decision making in sports.
Smeeton, N. J., Williams, A. M., Hodges, N. J., & Ward, P. (2005). The relative effectiveness of various instructional approaches in developing anticipation skill. J Exp Psychol Appl, 11(2), 98-110.
Vinter, A., & Detable, C. (2008). Implicit and explicit motor learning in children with and without Down’s syndrome. British Journal of Developmental Psychology, 26(4), 507-523. doi: 10.1348/026151007×267300
Wilson, M. (2008). From processing efficiency to attentional control: a mechanistic account of the anxiety–performance relationship. International Review of Sport and Exercise Psychology, 1(2), 184-201.