Laws Of Movement Learning And Control

Various  laws  of  movement  learning  and  control have  been  proposed  on  the  basis  of  research.  In this entry, the focus is on three of the most firmly established  of  these  laws:  the  law  of  practice, Fitts’s law, and Hick’s law. These laws are of interest  to  sport  and  exercise  psychologists  because they specify relatively simple relationships between different  variables  related  to  movement  learning and control. The defining feature of these laws is that  the  relationships  they  specify  apply  to  many different populations (e.g., males and females, the young and the elderly) and types of movement in sport  and  exercise.  The  laws  are  useful  because they  afford  the  identification  of  practice-related conditions  that  promote  movement  learning  and predictions about how individuals will perform in various  situations  requiring  movement.  As  such, the  laws  provide  a  basis  for  the  design  of  practice and training curricula, schedules, and environments  and  also  for  the  design  of  equipment  for sport  and  exercise.  The  laws  are  described  here, in turn.

The Law of Practice

The law of practice states that more practice of a motor task will lead to more learning of that task. This definition is usually accompanied by a second statement:  Changes  in  motor  task  performance that follow practice are generally large and rapid at first and become gradually smaller with continued  practice.  As  an  example,  consider  a  scenario in  which  30  novice  gymnasts  are  each  provided with  10  practice  sessions,  in  which  the  gymnast attempts  to  stand  one-footed  on  the  beam,  with the other leg bent at the knee, without wobbling or falling off the beam. Each practice session is separated  by  a  3  days’  rest,  lasts  2  hours,  and  begins with one test of how long, in seconds, the gymnast can  do  the  task  before  they  experience  an  obvious wobble or a fall. Consider then that the average of the 30 gymnasts’ test scores is calculated for each  of  the  10  days’  tests  and  the  average  values are plotted on a graph against the practice sessions undertaken. The law of practice predicts that the graph  would  look  something  like  the  (hypothetical) example graph shown in Figure 1. Note from the  graph  that,  consistent  with  the  law  of  practice, the increase in time spent balanced one-footed on the beam is greatest early in practice, between Practice  Sessions  1  and  2,  and  becomes  smaller with  more  practice;  the  smallest  increase  occurs between Practice Sessions 9 and 10. One interpretation of this effect is that the rate of improvement at any point in practice is determined by how much learning  remains.  Early  in  the  practice  of  a  given task, much remains to be learned and thus the rate of learning is very rapid. After extensive practice, there is not much left to be learned, so learning is much slower. At this late stage of learning, it can take months or even years of practice before any noticeable gain in performance is attained. As with all of the laws described here, the law of practice applies to many different populations and types of are often practiced in isolation from other components of the sport, which affords an increase in the rate of attempts to practice the component; a tennis player might devote an entire practice session to practicing her backhand volley.

Thus, the deliberate practice of a task contrasts with  mere  engagement  in,  and  experience  of,  a task.  A  common  example  of  this  difference  concerns  golf.  A  golfer  seeking  to  improve  his  game adds a nine-hole round with friends to his weekly golf  schedule,  which  he  considers  extra  practice but no improvement in his game results. On closer inspection,  however,  the  holes  are  played  in  a relaxed  way  and  the  “practice”  session  lacks  the qualities  of  deliberate  practice.  Thus,  this  golfer’s       addition of nine holes to his weekly golf schedulemovement task, from turns in skiing to throws in discus.


Figure 1   A Hypothetical Example Demonstrating the Relationship Between Task Performance (Time Spent Balanced One-Footed on a Gymnastics Beam) and Amount of Practice as Predicted by the Law of Practice

It is important to define practice in relation to the  law  of  practice.  Practice  activities  can  differ widely, and these differences are not always appreciated, leading some individuals to engage in what they  consider  to  be  practice  activities  only  to  be disappointed  when  little  or  no  learning  follows. While  the  exact  qualities  of  practice  activities affording  optimal  learning  in  sport  and  exercise are  in  contention,  Anders  Ericsson  and  his  colleagues  have  proposed  the  term  deliberate  practice  to  capture  some  of  the  qualities  that  appear associated  with  learning.  Deliberate  practice  is structured, purposeful practice relevant to improving  performance.  It  requires  concentration  and/ or  effort  and  is  often  undertaken  alone  to  allow the  learner  to  concentrate;  these  characteristics make the process of engaging in deliberate practice inherently unenjoyable, even if the result of deliberate practice is enjoyable, such as the acquisition of  a  new  skill.  Deliberate  practice  activities  are often  focused  on  improving  weaker  components of current performance—for example, a backhand volley  in  tennis.  Coaches  are  often  employed  to identify  these  components  and  prescribe  specific deliberate practice activities to improve them— for example,  drills  to  practice  backhand  volleys  at various distances from the net. These components affords him the opportunity to obtain more experience of the game but does not involve its deliberate practice. Hence, there is no improvement in the golfer’s game.

Fitts’s Law

Fitts’s  law  describes  in  more  formal  terms  what is known in everyday terms as the speed-accuracy trade-off;  that  is,  it  describes  the  relationship between  the  speed  of  a  movement  and  its  accuracy. In the 1950s, researcher Paul Fitts created an experiment  in  which  two  targets  were  laid  upon a table-type surface in front of a participant; one target  was  positioned  slightly  to  the  left  of  the participant and the other slightly to the right. The participant’s task was simply to tap anywhere on the  surface  of  the  left  target  and  then  the  right target  using  a  stylus,  which  was  a  penlike  rod, held  in  one  hand,  and  then  repeat  this  (i.e.,  left target,  right  target,  left  target)  as  fast  as  possible for  a  specific  time  such  as  30  seconds.  The  task was  like  hitting  one  drum  with  a  drumstick,  and then  another  drum  (with  the  same  drumstick  in the same hand), then the first drum, and so on, as fast  as  possible.  In  the  experiment,  the  width  of the two targets could be varied; for example, they each  might  be  small,  at  2  cm  in  width,  or  large, at 10 cm in width. Also, the distance between the targets  could  be  varied;  for  example,  they  might be  closely  spaced,  with  10  cm  between  them,  or farther apart, with 20 cm between them. The task was scored as the number of taps the participant could  make  in  the  time  allowed.  Accuracy  was stressed  by  asking  the  participant  to  make  sure that  no  more  than  5%  of  the  taps  fell  outside  of a  target.  Fitts  calculated  the  average  time  taken between two consecutive taps by dividing the time over  which  the  participant  was  requested  to  tap (e.g., 30 seconds) by the number of taps made: If30 taps were made in 30 seconds, the average time between 2 consecutive taps was 1 second. In other words, it took the participant a second on average to tap one target and then move his or her hand to the other target and tap that target. Fitts called this variable movement time (MT).

Fitts explored what happened to MT when the width of each target and the distance between the targets was varied. When targets at a fixed distance apart  (e.g.,  10  cm)  each  had  their  width  reduced (e.g., from 4 cm to 2 cm), MT increased; participants appeared to need to move slower to be more accurate  in  the  spatial  positioning  of  their  taps. Also,  when  targets  of  a  fixed  width  (e.g.,  4  cm) were  moved  farther  apart  (e.g.,  from  10  cm  to20 cm), MT slowed. Participants appeared to need to  take  longer  to  move  their  hand  over  the  extra distance if they were to maintain the spatial accuracy  of  their  tapping.  While  these  findings  were interesting,  Fitts’s  really  important  finding  was that MT increased by a constant amount whenever the  distance  between  the  targets  was  doubled  or the  size  of  each  target  was  halved.  Furthermore, this finding was basically the same for all the participants tested. This meant that Fitts was able to predict, with reasonable accuracy, the MT of participants he had not yet tested, based simply on the width  of  the  targets  and  their  distance  apart.  Of course, not every task involving movement is like Fitts’s tapping task, but since his research, studies involving different populations and different types of movement task have yielded findings consistent with his own. These consistent findings have led to Fitts’s early observations being considered a law of motor control.

One explanation for Fitts’s law, in simple terms, is as follows. An increase in the speed with which a  given  limb  (e.g.,  an  arm)  is  moved  requires  an increase in the impulse applied by the muscles to that  limb;  note  that  an  impulse  is  the  amount  of force applied multiplied by the time for which that force  is  applied.  A  characteristic  of  the  human movement  system  is  that  there  is  a  slight  and unavoidable  difference  between  the  impulse  an individual  intends  to  apply  to  a  limb  to  make  it move and the impulse that the individual actually applies to the limb. This difference can be considered  error.  Research  has  indicated  that  the  larger the impulse applied, the greater the error. Now let us  put  these  separate  statements  together:  When humans attempt to move a limb faster, they must apply a larger impulse to the limb: The larger the impulse  applied  to  the  limb,  the  larger  the  error in the impulse applied; the larger the error in the impulse applied, the greater the inaccuracy in the spatial positioning of the limb.

While  tasks  involving  simple  movements  like Fitts’s  tapping  task  offer  the  researcher  a  chance to  study  motor  control  under  controlled  laboratory  conditions,  these  movements  might  seem  at first glance to be of limited relevance to sport and exercise.  However,  simple  movements  form  the basis  for  the  more  complicated  movements  made in  sport  and  exercise  and,  as  such,  Fitts’s  law  is reflected  in  sport and  exercise-related  movements. For example, pole-vaulters take a long time to  learn  to  place  the  pole  tip  into  the  box  (i.e., the  hole  in  the  ground)  correctly  at  speed;  until then,  they  use  a  shorter  approach,  which  affords a  relatively  slow  approach  run,  to  achieve  an accurate tip placement. In addition, rock climbers who attempt to reach up very quickly to grab the next  hold,  because  they  feel  their  other  points of contact with the rock are tenuous, are less likely to  accurately  place  their  fingers  on  the  desired hold.

Hick’s Law

Hick’s law describes the relationship between the time  taken  to  prepare  a  movement  response  and the  number  of  possible  movement  response  alternatives.  In  more  everyday  terms,  the  law  states that individuals are slower to react when required if  it  is  not  clear  before  they  are  required  to  react exactly how they should react—that is, if it is not clear what kind of movement response is required. An example of Hick’s law can be seen in football. Consider  a  down  in  which  the  defense  is  unclear about what type of offensive play the opponent is likely to run: When the ball is snapped, the defense will be relatively slow to react with an appropriate response. In contrast, if the defense knows exactly what offensive play the opponent is going to run, the defense will be relatively fast to react with an appropriate response when the ball is snapped.

In the 1950s, researchers William Edmund Hick and Ray Hyman studied reaction time (RT) using what  has  become  known  as  a  “choice  reaction time” task. In one type of this task, the participant is  seated,  with  one  hand  laying  palm-down  on  a “response panel,” and each of the four fingers of the hand resting on a separate button mounted in the  panel.  In  front  of  the  participant,  four  lights are presented in a row (i.e., horizontally) at head height.  Each  light  is  considered  a  stimulus,  to which the participant must respond as fast as possible  with  a  movement.  Specifically,  when  a  light is lit, the participant must press the button, from the four available, that corresponds to the lit light. Thus, if the leftmost light is lit, she must press the leftmost  button  with  her  index  finger  (if  she  is right-handed), whereas if the rightmost light is lit, she must press the rightmost button with her little finger, and so on. Usually, participants are unable to predict exactly which light will be lit or when it will be lit and thus are unable to initiate a response in advance of a light being lit. RT is measured as the time taken from a light being lit to the beginning  of  the  participant’s  finger  movement  on  the button.

In the choice RT task presented previously, there were  four  “stimulus–response”  (S–R)  choices  or alternatives;  that  is,  the  participant  could  be  presented with one of four stimuli, and each of these stimuli  required  a  unique  response.  For  example, when the second-to-left light was lit, a press of the second-to-left  button  was  required  by  the  middle finger.  Hick  and  Hyman  studied  the  relationship between  RT  and  the  number  of  S–R  alternatives by presenting various numbers of lights associated with  an  equal  number  of  buttons  to  be  pressed. One  study  condition  presented  to  the  participant might feature two S–R alternatives, involving two lights  and  two  buttons,  whereas  the  next  study condition presented might involve four S–R alternatives, as in the previous example. The researchers  found  that  RT  slowed  as  the  number  of  S–R alternatives increased. In other words, when it was less clear how they would be required to respond, participants were slower to react.

However, Hick and Hyman’s findings extended beyond  identifying  that  RT  slowed  under  these circumstances.  What  these  researchers  discovered was that RT slowed by a constant amount, which was  approximately  150  milliseconds  on  average for the type of choice RT task described here, every time the number of S–R alternatives was doubled. Of course, RT was also quickened by this amount every  time  the  number  of  S–R  alternatives  was halved.  Thus,  when  a  “one  light  and  one  button condition” was changed to a “two lights and two buttons”  condition,  RT  slowed  by  150  milliseconds  on  average,  and  when  an  “eight  lights  and eight  buttons”  condition  was  changed  to  a  “two lights and two buttons” condition, RT quickened by 300 milliseconds on average.

Researchers have found that Hick and Hyman’s findings apply to different populations and different types of movement task, which has led to the finding  being  considered  a  law  of  motor  control. One  explanation  for  Hick’s  law,  in  simple  terms, is that, when there are more S–R alternatives, the participant  must  process  (i.e.,  think  about)  more information to be able to identify and produce the appropriate response. As humans can only process a  limited  amount  of  information  in  a  given  time, RT is slower when there is more information to be processed.

As with Fitts’s law, the choice RT task described here might seem at first glance to be of limited relevance to movements made in sport and exercise. However, Hick’s law helps explain performance in real  sports,  especially  sports  in  which  responding faster conveys a performance advantage. Consider a defensive team in football that knows the opponent’s offense has two key running plays and two key passing plays and then observes the opponent’s only ball carrier get injured so that running plays are no longer an option. At the line of scrimmage, the  defense  knows  there  are  now  only  two  possible play options, not four. In terms of Hick’s law, the  number  of  S–R  alternatives  has  been  halved, affording  the  defense  a  quicker  RT  (by  150  milliseconds) at the snap. Hick’s law is also reflected in findings from studies of skilled athletes’ preparation  for  upcoming  competitions.  For  example, David Eccles and his colleagues presented evidence that  skilled  athletes  gather  information  affording  the  identification  of  (and  thus  a  reduction  in uncertainty  about)  the  types  of  stimuli  that  will be presented during a competition. An example of this  process  is  when  athletes  and  coaches  in  soccer  or  football  watch  game  film  of  an  upcoming opponent  to  identify  patterns  of  play  unique  to that  opponent  or  when  kayakers  and  orienteers explore the river and forest, respectively, in which they will compete (under time pressure) to identify in advance the demands unique to these environments. According to Hick’s law, these information gathering  activities,  which  reduce  uncertainty about  the  types  of  stimuli  that  will  be  presented during a competition, lead to quicker RTs during that competition.


In  conclusion,  there  are  three  well-established laws  of  movement  learning  and  control:  the  law of practice, Fitts’s law, and Hick’s law. The law of practice  describes  the  relationship  between  practice and learning; Fitts’s law describes the relationship between movement speed and accuracy; and Hick’s law describes the relationship between the time  taken  to  prepare  a  movement  response  and the  number  of  possible  movement  response  alternatives. The relationships described by these laws apply to many different populations and types of movement in sport and exercise. The laws afford the  identification  of  practice-related  conditions that  promote  movement  learning  and  predictions about  how  individuals  will  perform  in  situations requiring movement. As such, the laws are fundamental within the discipline of sport and exercise psychology (SEP).


  1. Eccles, D. W., Ward, P., & Woodman, T. (2009). The role of competition-specific preparation in expert sport performance. Psychology of Sport and Exercise, 10,96–107.
  2. Ericsson, K. A., Krampe, R. Th., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363–406.
  3. Lee, T. D. (2011). Motor control in everyday actions.Champaign, IL: Human Kinetics.
  4. Magill, R. A. (2007). Motor learning and control: Concepts and applications. New York: McGraw-Hill.
  5. Schmidt, R. A., & Lee, T. D. (2011). Motor control and learning: A behavioral emphasis (5th ed.). Champaign, IL: Human Kinetics.

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