Learning in Sport

The  ability  to  learn  defines  much  that  is  unique about human behavior and underlies many aspects of sport and exercise psychology (SEP). Attempts to  develop  sweeping  laws  of  learning  have  generally  been  unsuccessful,  and  it  is  unlikely  that a  universal  theory  of  learning  can  be  developed. Learning  is  often  described  as  a  process  during which  lasting  changes  occur  in  the  potential  that an  individual  has  for  a  specific  behavior.  Such changes  are  a  consequence  of  experience  within a  particular  environment,  rather  than  attributes of  growth  or  development  or  temporary  changes caused by fatigue, boredom, injury or even drugs or aging. Some authors define learning as a “biological  device”  that  facilitates  primarily  adaptive changes  that  extend  an  individual’s  capability  to survive.

This entry provides a much-condensed summary of learning as it has been understood over the past120 years of study. Influential concepts and theories of learning are discussed in a relatively chronological sequence, and an effort is made to show how the theories culminate in recent approaches to learning in sport and exercise. Behaviorist theories regard  learning  to  be  an  observable  effect  of  the environment  on  an  organism’s  behavior,  whereas cognitive  theories  regard  learning  to  be  relatively permanent  storage  of  knowledge  as  processes  or representations  in  the  brain.  Constructivist  theories consider learning to be the active construction of  knowledge  about  the  world.  Jerome  Bruner (1915–  ),  for  example,  argued  that  learning  is primarily driven by an active process of discovery about the meaning of information.

Learning by Association

A forerunner to any of these approaches, and probably  the  firstborn  theory  of  learning,  held  that learning  was  a  consequence  of  the  formation  of associations through experience. A person may feel pain on the first occasion that he or she goes running and thereafter associate exercise with pain as a  consequence  of  learning  the  stimulus–response (S–R)  relationship.  Learning  by  association  primarily  is  a  function  of  conditioning.  Ivan  Pavlov (1849–1936)  first  demonstrated  this  as  classical conditioning. By presenting food at the same time that  he  sounded  a  bell,  Pavlov  conditioned  dogs to  associate  the  idea  of  food  with  the  sound  of  a bell. The dogs thereafter salivated when they heard a  bell,  regardless  of  whether  food  was  present. Pavlov’s  work  paved  the  way  for  behaviorism,  as conceptualized by John Watson (1878–1959), who rejected  subjective  inferences  about  the  influence of cognition on behavior in favor of objective measurement of external, overt actions. Watson argued that conditioning is the key mechanism that underlies  learning  in  animals  and  humans.  He  argued that all are born tabula rasa (a blank slate), and the environment  governs  how  each  learns  to  behave. Watson  (1930)  famously  claimed  that  the  aim  of psychology is “to predict, given the stimulus, what reaction will take place; or, given the reaction, state what  the  situation  or  stimulus  is  that  has  caused the reaction” (p. 11).

Shaping to Learn

An important building block of behaviorism was provided  by  Edward  Thorndike’s  (1874–1949) “Law  of  Effect,”  which  states  that  behaviors are  likely  to  be  repeated  if  they  are  followed  by favorable  (e.g.,  pleasant)  consequences  but  will eventually  cease  if  they  are  followed  by  unfavorable (e.g., disagreeable) consequences. Thorndike showed  that  cats  trying  to  reach  a  food  outside a puzzle box eventually pressed a lever that gave them access to the food and that over trials they became faster at pressing the lever because of the favorable outcome associated with that response. In  essence,  the  cats  had  learned  from  the  consequences  of  their  behaviors.  Thorndike’s  work gave  rise  to  operant  (instrumental)  conditioning, as  demonstrated  by  B.  F.  Skinner  (1904–1990). Skinner  showed  that  behaviors  could  be  modified  by  the  type  of  consequence  that  followed  a desired response. That is, a behavior would occur with  greater  frequency  if  it  was  reinforced  and with less frequency if it was punished or even be extinguished if there was no consequence. Skinner also  showed  that  behaviors  could  be  gradually modified  (shaped)  by  reinforcing  iterations  that approximated the desired response. Coaches often use shaping to modify an inappropriate technique in sport, or chaining to link appropriate responses together. A coach might use verbal praise to reinforce  gradual  increases  in  the  height  of  the  ball toss  when  a  child  serves  at  tennis,  for  example, and  chaining  might  involve  linking  the  ball  toss to  knee  bend,  followed  by  the  swing  of  the  tennis racquet, the snap of the wrist at contact, and finally the follow-through.

Many criticisms have been directed at behaviorism. For example, even when a behavior has been learned  through  conditioning,  individuals,  and animals,  clearly  can  change  the  behavior  if  new information  becomes  available.  Gestalt  psychology abandoned the step-by-step S–R approach to learning in favor of an approach in which behaviors  were  seen  to  be  driven  by  dynamic  patterns of  information  available  in  the  environment  as  a whole.  But  the  great  criticism  of  behaviorism,  as embodied  in  Sigmund  Freud’s  (1836–1939)  psychodynamic  approach,  was  that  by  considering only objective, observable behaviors, behaviorism ignored the influence of cognition, internal mental states of mind, on behavior.

Thinking to Learn

Cognitive  approaches  to  learning  differ  from  the behaviorist approach in that they define learning in terms of relatively permanent changes in organization and storage of information as a consequence of  experience,  rather  than  relatively  permanent changes  in  behavior  itself.  Consequently,  internal  mental  processes,  such  as  information  encoding  and  processing,  perception  and  memory,  and insight  or  intuition  are  seen  to  be  key  factors  in learning, which mediate the relationship between a stimulus and a response.

Cognitive theories therefore try to account for the  influence  of  internal  thought  processes  on learning.  Albert  Bandura  (1925–  )  proposed  that internal psychological factors (the person), external observational factors (behavior), and the situation all interact to influence social-interpersonal forms  of  learning.  Social  learning  theory,  now called  social  cognitive  theory  (SCT),  proposed that  most  learning  occurred  observationally,  via modeling, and the tendency for a person to persist at it was governed by factors such as the person’s sense  of  their  own  capability  to  carry  out  the required behavior effectively (i.e., self-efficacy).

Multistore  models  of  memory  that  propose separate   sensory,   short-term,   and   long-term stores for information and multicomponent models  of  memory  that  explain  how  task-relevant information  is  temporarily  stored  and  manipulated  have  provided  a  popular  framework  for examining  the  role  of  internal  mental  processes in  learning.  Evidence  suggests  that  long-term memories  (LTMs)  present  as  rewired  patterns  of activation that require a process of consolidation to be laid down permanently, whereas short-term memories  present  as  patterns  of  neural  activation  that  are  somehow  prolonged  by  working memory mechanisms such as subvocal rehearsal. Working memory facilitates a crucial component in  most  cognitive  approaches  to  learning,  which is  verbal  hypothesis  testing  about  contingencies associated with actions, especially in terms of reasoning  and  problem  solving.  B.  F.  Skinner  even delineated  between  rule-governed  behavior  and contingency-shaped  behavior,  because  behaviorist approaches have difficulty accommodating the tendency  for  humans  to  verbally  mediate  behavior.  Skinner  argued  that  behaviors  that  solve  a problem can arise from direct shaping by contingencies (operant condition) or from rules that are hypothesized  by  the  person  solving  the  problem or  from  instructions  provided  by  an  agent  with prior experience of the problem. In sport, a particular  behavior  may  be  shaped  gradually  by  its consequences  or  by  verbal  rules  that  the  athlete acquires  by  hypothesis  testing  or  by  instructions from  a  coach  who  has  previously  acquired  the relevant information.

Conscious and Unconscious Awareness of Learning

An  important  distinction  that  arises  from  the cognitive  approach  to  learning  is  between  conscious and unconscious aspects of behavior, most recently approached within the context of implicit and  explicit  learning.  Much  of  our  interaction with  the  environment  is  implicit,  resulting  in accrual  of  knowledge  without  conscious  awareness and sometimes without even intent to learn. Experimental studies of implicit learning began in the  1960s,  when  Arthur  Reber  used  Markovian grammar  chains  to  study  the  way  in  which  participants  learned  knowledge  underlying  complex  tasks.  When  participants  memorized  lists  of exemplars  (letter  strings)  created  using  the  artificial  grammars,  they  could  distinguish  between grammatically  correct  and  incorrect  exemplars that  they  had  not  seen  previously,  even  though they  were  unable  to  consciously  express  knowledge of the grammatical rules that supported their decisions.

The  double  dissociation  between  performance of a task and the ability to express knowledge that guides  performance  of  that  task  has  been  demonstrated using other paradigms. For example, in the serial reaction time task (SRTT), participants are  required  to  rapidly  depress  keys  that  match positions indicated on a monitor. When the same sequence  of  positions  (usually  about  12–15)  is repeated on trials, participants learn to anticipate each  position  in  the  sequence  and  thus  respond by  depressing  the  matching  keys  very  rapidly. Few  participants  become  consciously  aware  that they are responding to a specific sequence of key presses  and  fewer  still  can  report  the  sequence, suggesting  that  the  sequence  may  have  been learned implicitly.

Implicit and Explicit Motor Learning

The  conscious  and  unconscious  dichotomy  has been applied to learning in SEP in the context of implicit and explicit motor learning. Left to their own devices, humans display a pervasive tendency to  acquire  declarative  knowledge  explicitly  when they learn motor skills. Usually, this knowledge is accrued  by  instructions  from  an  agent  (such  as  a teacher  or  coach)  and  conscious  hypothesis  testing  during  a  trial-and-error  process  in  which  the learner  makes  attempts  to  move  in  a  way  that solves  the  motor  problem.  In  particular,  visual feedback  about  the  outcome  of  each  attempt  is used to confirm or refute the hypotheses that are tested.  Take,  for  example,  a  father  and  son  at  a golf driving range. The father may instruct his son to hold the golf club in a particular way. The son may  use  this  grip  but  see  that  the  ball  travels  to the left. Consequently, the son may try a different grip and watch closely to see if the ball travels in the desired direction. If the grip works, it is likely that  the  information  will  be  stored  as  declarative knowledge for further use.

The  ability  to  test  hypotheses  and  store  and manipulate   information   that   can   be   used   to make  motor  responses  is  made  possible  by  the information-processing  capabilities  of  working memory. Implicit motor learning tries to discourage hypothesis  testing  about  motor  responses  or  disrupt working memory storage of information that can be used for hypothesis testing, thereby limiting the amount of declarative knowledge that is accumulated during learning. For example, when motor learners  carry  out  a  secondary  working  memory task, such as tone counting or random letter generation, they tend to be unable to test hypotheses about the  primary  motor  task  that  they  are  practicing. Consequently,  they  learn  the  primary  motor  task implicitly. Other methods devised in the context of SEP cause implicit motor learning by reducing the commission of errors during practice or providing reduced feedback about the outcomes of the movement.  These  methods  prevent  working  memory involvement in learning by removing the necessity or the ability, respectively, to test hypotheses. If a performer does not make an error when executing a movement, there is little point in testing a hypothesis; if a performer does not become aware of the outcome  of  each  movement,  it  is  not  possible  to test the outcome of a hypothesis. Another method that  has  been  used  to  facilitate  implicit  motor learning entails presentation of a movement analogy  (e.g.,  “kick  like  a  dolphin”),  which  describes an appropriate technique by which to achieve the desired  movement  response,  without  the  need  to present  explicit  instructions.  Analogy  learning  is only effective if the similar concept upon which it is based (a dolphin’s tail movement) is understood by the learner. While it is unlikely that any form of human motor learning is purely implicit or explicit, implicit motor learning techniques appear to reduce conscious  access  to  task-relevant  knowledge  and thus  reduce  potential  destabilization  of  automatic movement by conscious thought processes.


  1. Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence & J. T. Spence (Eds.), The psychology of learning and motivation: Advances in research andtheory (Vol. 2, pp. 89–195). New York: Academic Press. Baddeley, A. D., & Hitch, G. J. (1974). Working memory. In G. A. Bower (Ed.), Recent advances in learning and motivation (Vol. 8, pp. 47–89). New York: Academic Press.
  2. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall.
  3. Bruner, J. (1960). The process of education. Cambridge, MA: Harvard University Press.
  4. Masters, R. S. W., & Maxwell, J. (2008). The theory of reinvestment. International Review of Sport and Exercise Psychology, 1, 160–183.
  5. Masters, R. S. W., & Poolton, J. M. (2012). Advances in implicit motor learning. In N. J. Hodges & A. M. Williams (Eds.), Skill acquisition in sport: Research, theory and practice (2nd ed., pp. 59–75). London: Routledge.
  6. Pavlov, I. P. (1927). Conditioned reflexes: An investigation of the physiological activity of the cerebral cortex (G. V. Anrep, Trans. & Ed.). London: Oxford University Press.
  7. Reber, A. S. (1967). Implicit learning of artificial grammars.Journal of Verbal Learning and Verbal Behavior, 5,855–863.
  8. Skinner, B. F. (1984). An operant analysis of problem solving. The Behavioral and Brain Sciences, 7,583–613.
  1. Thorndike, E. (1932). The fundamentals of learning.New York: AMS Press.
  2. Watson, J. (1930). New York: Norton.

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