Psychology of Learning

Module 08: Sports Psychology

Part 1: Motor Learning Fundamentals

Looking Back

Throughout this course, we’ve explored how organisms learn through classical & operant conditioning—how neutral stimuli become conditioned through pairing, how behaviors change based on consequences, & how organisms optimize choices. But there’s a critical component underlying all learning we haven’t systematically addressed: the physical capacity to perform behaviors. Motor skills are required for all types of learning. We cannot reinforce a behavior an animal is incapable of performing, & a person with motor impairments faces challenges demonstrating learned behaviors. Understanding how motor skills are acquired, refined, & transferred provides essential foundations for applying learning principles in education, sports, rehabilitation, & everyday skill development.

The Foundation of All Learning: Motor Control

Motor learning isn’t separate from other forms of learning—it’s foundational to them. Every behavior we condition, every response we reinforce, every skill we practice requires motor execution. Athletes learning complex routines, musicians mastering instruments, surgeons developing precise techniques, children learning to write—all depend on motor learning principles. Sports psychology applies these principles to optimize athletic performance, examining how physical & mental training combine to produce excellence.

The Variety of Motor Skills

Not all motor skills are created equal. Understanding different types of motor skills helps us apply appropriate training methods & set realistic expectations for learning rates.

Discrete motor skills are movements that are completed shortly after they are begun. These skills have definite beginning & ending points. Examples include throwing a ball, hitting a tennis serve, pressing a piano key, or pulling a trigger. Each action is distinct & separate from the next (Schmidt & Lee, 2011).

Continuous motor skills are movements that extend indefinitely over time. These skills flow without clear beginning or ending points. Examples include swimming, running, steering a car, or tracking a moving target with your eyes. The movement continues as long as needed (Schmidt & Lee, 2011).

Open-Loop Versus Closed-Loop Movements

Closed-loop movement is movement whereby the individual continually receives & can react to feedback about whether the movement is proceeding correctly. The person monitors ongoing performance & makes adjustments in real-time. Examples include slowly reaching for a cup while watching your hand, carefully threading a needle, or adjusting your steering while parking (Adams, 1971).

Open-loop movement is movement performed without the aid of feedback. Once initiated, the movement proceeds without modification based on sensory information. Examples include quickly swatting a fly, executing a well-practiced golf swing, or typing on a keyboard without looking. These movements are too fast for feedback to influence them during execution (Schmidt, 1975).

The distinction between closed-loop & open-loop movements has important implications for learning. Beginners rely heavily on closed-loop control, constantly monitoring & adjusting movements. As skills develop, movements become more open-loop—executed rapidly without conscious monitoring. Expert typists don’t watch each key press; experienced drivers shift gears automatically; skilled musicians execute rapid passages without thinking about individual notes. The transition from closed-loop to open-loop control marks skill mastery.

Reinforcement & Knowledge of Results: What Makes Motor Learning Work?

The Law of Effect & Motor Learning

Thorndike (1927) extended his law of effect to motor learning through a simple but elegant experiment. Thorndike had blindfolded humans draw lines intended to be exactly 3 inches long. The experimental group was told “Right” if the line was within 1/8 inch of 3 inches & “Wrong” if off by more than 1/8 inch. The control group was told nothing about their performance.

Results were dramatic: The experimental group’s accuracy improved substantially across trials. The control group showed no improvement whatsoever. This demonstrated that reinforcement following motor responses strengthens those responses, just as reinforcement strengthens operant behaviors. But Thorndike’s interpretation—that “Right” & “Wrong” functioned as reinforcers—was soon challenged.

What Can Be Better Than Reinforcement?

Knowledge of results (KR) is, in motor-skill learning, feedback given to the learner about how close their movement came to the goal. KR provides information about performance outcomes (Thorndike, 1927).

Subsequent research revealed that information, not reinforcement per se, is the critical component of motor learning. When experimenters provided detailed information about performance—”You were 2 inches too long” or “You were 0.5 inches too short”—learners improved even faster than with simple “Right/Wrong” feedback. Reinforcement’s emotional impact matters less than the informational content about how to adjust future attempts.

This finding has profound implications: Motor learning proceeds best when learners receive precise, informational feedback rather than evaluative praise or criticism. Telling a basketball player “Great shot!” is less useful than “Your release point was 2 inches higher than usual.” Information enables correction; evaluation provides emotional response without guidance for improvement.

Different Ways to Deliver Knowledge of Results

How often should KR be provided? Winstein & Schmidt (1990) addressed this question in an influential study. They gave some participants feedback on 67% of trials & some on 100% of trials. During initial learning, constant feedback (100%) produced better performance—learners improved more quickly with more information.

But here’s the surprising finding: During a follow-up test 2 days later when no feedback was provided, the 67% feedback group performed better! Why? Constant feedback creates dependency—learners rely on external information rather than developing internal error-detection capabilities. Reduced feedback forces learners to evaluate their own performance, building self-monitoring skills that persist when feedback is removed.

This has practical implications for coaching & instruction: Provide frequent feedback during early learning to establish correct movement patterns, then gradually reduce feedback frequency to promote independence. Athletes need to perform without coaches constantly providing input; students need to self-evaluate; patients in rehabilitation need to monitor their own movements. Intermittent feedback builds self-sufficiency.

Delaying Knowledge of Results

Timing matters in feedback delivery. In tasks where we normally receive immediate feedback, slight delays cause disruption. If we hear our voice even slightly after speaking, we begin to stutter. Try using two different phones at the same time where one has a slight delay—speaking becomes nearly impossible. The delayed auditory feedback conflicts with expected timing, disrupting motor control.

However, for skills where feedback isn’t naturally immediate—like archery, where you shoot then walk to the target to see results—brief delays don’t impair learning. The key is whether the delay violates natural feedback timing. Activities with inherently delayed feedback (golf—hit the ball, then see where it lands) accommodate delays better than activities with immediate natural feedback (typing—see letters appear as you press keys).

Knowledge of Performance: Going Beyond Outcomes

Knowledge of performance (KP) is the delivery of information about the sequence of components of a complex movement. Rather than just indicating whether the outcome was correct, KP provides feedback about the process—how the movement was executed (Gentile, 1972).

Consider a basketball free throw. KR tells you whether the ball went in (outcome). KP tells you that your elbow was too far out, your release point was too low, & your follow-through was incomplete (process). KR says what happened; KP says why it happened & how to fix it.

Conclusion: Knowledge of performance produces greater improvements than knowledge of results. While KR has value, KP’s detailed process information enables more targeted corrections. Effective coaching emphasizes KP—helping athletes understand not just that performance was suboptimal, but specifically which movement components need adjustment. Video analysis in sports exploits this principle, allowing athletes to see & correct specific movement flaws rather than just knowing the outcome was unsatisfactory.

Recent meta-analytic evidence supports the superiority of KP approaches. Han, Syed Ali, & Ji (2022) analyzed 15 studies examining feedback effects on motor skill learning in physical education. Their findings confirmed that feedback significantly improves motor skill acquisition, but the format matters as much as its presence. Visual feedback & combined visual-verbal feedback were most effective, while verbal feedback alone showed weaker effects. Both expert model observation & self-model video feedback promoted skill development. These findings reinforce that showing learners what their movements look like—the essence of KP—produces better outcomes than simply telling them whether they succeeded or failed.

Distribution of Practice: Massed Versus Spaced Training

Distributed practice is a training procedure in which fairly brief practice periods alternate with rest periods. Practice sessions are spaced out over time (Ebbinghaus, 1885).

Massed practice is a training procedure in which practice takes place in one continuous block without rest periods. The learner practices extensively in a single session (Ebbinghaus, 1885).

Research consistently demonstrates that distributed practice produces superior motor learning compared to massed practice. Athletes who practice 1 hour per day for 6 days learn more effectively than those who practice 6 hours in a single day. Musicians who practice 30 minutes twice daily progress faster than those practicing 1 hour once daily.

Why? Several factors contribute: (1) Fatigue accumulates during massed practice, reducing practice quality. (2) Distributed practice allows time for memory consolidation between sessions. (3) Spacing provides opportunities for mental rehearsal between sessions. (4) Varied contexts across sessions enhance generalization. (5) Rest periods prevent overuse injuries.

Practical applications: Structure athletic training with rest days. Schedule music practice across multiple short sessions rather than marathon sessions. Design rehabilitation protocols with breaks between exercises. Students learning laboratory techniques benefit from distributed sessions across weeks rather than intensive weekend workshops. The spacing effect—one of psychology’s most robust findings—applies powerfully to motor learning.

Observational Learning of Motor Skills

Observational learning can be beneficial, especially when combined with direct practice. When pairs of participants take turns practicing balancing on an unstable platform, they perform better than people who practice in isolation for the same amount of time. Watching others provides information about successful & unsuccessful strategies, movement patterns to emulate or avoid, & timing of movements.

Modeling is extensively used in sports instruction. Coaches demonstrate proper techniques; athletes study videos of elite performers; dance students watch accomplished dancers. However, observation alone produces minimal learning—it must be combined with physical practice. Watching someone swim won’t teach you to swim, but watching correct technique, then practicing, then receiving KP accelerates learning beyond practice alone.

Transfer of Training: Does Practice on One Task Help Another?

Transfer of training occurs when experience on one task affects performance on another task. This is similar to generalization in animal learning studies but specifically addresses motor skills (Thorndike, 1906).

Positive transfer occurs when practice on one task improves learning or performance on another task. The skills or knowledge from the first task facilitate the second task (Osgood, 1949).

Negative transfer occurs when practice on one task impairs learning or performance on another task. The first task creates interference or inappropriate habits for the second task (Osgood, 1949).

An Example of Positive Transfer: The Mirror Tracing Experiment

Whenever we learn a new skill, do we learn very specific movements, or do we learn general principles applicable in different situations? If a child learns that “A” is the symbol for the “ah” sound when written in one font, does that learning transfer when encountering “A” in different fonts, sizes, or handwriting styles? Transfer of training addresses how learning generalizes across variations.

Mirror tracing provides a classic demonstration of transfer. The task involves using a pencil to trace a maze while looking only at the reflection of your hand in a mirror—you cannot look at your hand directly. This creates a challenging situation where visual feedback is reversed: moving your hand right makes the reflection move left.

The Mirror Tracing Experiment: Detailed Design

General Task: Participants trace a star-shaped maze while viewing only the mirror reflection. The challenge is coordinating movements when visual feedback is spatially reversed.

Experimental Group Design:

• Training Phase: Trace the star maze in the mirror three times using the dominant hand. This allows learning of the general principle of mirror reversal & specific movements required for the task.
• Testing Phase: Trace the star maze in the mirror one time using the nondominant hand. This tests whether learning transfers across hands.

Control Group Design:

• No Training Phase: Control participants receive no practice with mirror tracing.
• Testing Phase: Trace the star maze in the mirror one time using the nondominant hand. This provides baseline performance for comparison.

We need the control group to determine whether the experimental group’s performance is “good” or merely represents baseline nondominant hand ability. Without controls, we couldn’t distinguish transfer effects from inherent ability.

Hypotheses & Predictions

Possible Hypotheses:

• Hypothesis 1: Learning mirror star tracing with the dominant hand involves learning the general principle of mirror reversal. Therefore, transfer to the nondominant hand should be substantial—perhaps even perfect. The cognitive understanding transfers completely.
• Hypothesis 2: Learning mirror star tracing with the dominant hand involves learning very specific muscle movements & motor programs for that hand. Therefore, minimal transfer should occur to the nondominant hand because different muscles & neural pathways are involved.
• Hypothesis 3: Learning involves both general principles (mirror reversal understanding) & specific motor programs. Therefore, partial transfer should occur—better than control group but not perfect.

Operational Definitions: Measuring Performance

We’ve established that transfer will be evident if the experimental group outperforms the control group during testing. But how do we measure mirror tracing ability?

Dependent Variable 1: Time to Complete the Maze. Mirror tracing ability might be reflected by how long it takes to trace the complete star. Faster completion suggests better skill. However, time alone is insufficient—rushing through produces errors.

Dependent Variable 2: Number of Errors. An error is counted any time the traced line touches or crosses the printed line boundaries. Fewer errors indicate better control. This captures accuracy independent of speed.

Using both measures provides comprehensive assessment. Ideal performance combines speed & accuracy. Some participants might trace quickly with many errors; others slowly with few errors. Both measures together capture skill level.

Predictions

If positive transfer occurs: The experimental group will complete the maze faster than the control group during testing. The experimental group will have fewer errors than the control group during testing.

Results typically show substantial positive transfer—experimental groups perform much better than controls. This demonstrates that motor learning includes learning general principles, not just specific muscle movements. The understanding of mirror reversal transfers even though different hand muscles execute the movements. However, transfer isn’t perfect—dominant hand practice doesn’t produce identical nondominant hand performance—indicating that specific motor programs also matter.

Ironic Errors in Movement: When Trying Not to Fail Causes Failure

Ironic errors theory, proposed by Wegner (1997), states that people have a tendency to make a false movement that they are trying hard to avoid, especially if their attention is distracted. The very act of trying not to do something increases the likelihood of doing it (Wegner, 1997).

Have you ever tried so hard not to spill a drink while carrying it that you became more likely to spill? Attempted so intensely to avoid hitting the golf ball into a water hazard that you hit it directly there? Told yourself “Don’t overthink this” only to overthink it? These are ironic errors—movements opposite to intentions that occur precisely because we’re trying to avoid them.

Wegner proposes that two cognitive processes operate: (1) An intentional operating process that tries to produce the desired behavior, & (2) An ironic monitoring process that searches for signs of failure. Under pressure or distraction, the monitoring process becomes dominant, making the unwanted behavior more salient & therefore more likely.

Sports applications abound: Basketball players told “Don’t miss this crucial free throw” become more likely to miss. Golfers thinking “Don’t slice” are prone to slicing. Figure skaters worried about falling are more likely to fall. Effective athletes learn to focus on what to do (positive instructions) rather than what to avoid (negative instructions). Coaches who emphasize “Make this shot” rather than “Don’t miss” facilitate better performance under pressure.

How This Material Relates to Sports Psychology

Sports applications abound: Basketball players told “Don’t miss this crucial free throw” become more likely to miss. Golfers thinking “Don’t slice” are prone to slicing. Figure skaters worried about falling are more likely to fall. Effective athletes learn to focus on what to do (positive instructions) rather than what to avoid (negative instructions). Coaches who emphasize “Make this shot” rather than “Don’t miss” facilitate better performance under pressure.

Motor learning principles are central to sports psychology because athletic performance depends not only on physical conditioning but also on how skills are acquired, refined, and transferred. Understanding discrete versus continuous skills, and closed‑loop versus open‑loop control, helps coaches design training programs that match the demands of specific sports. For example, closed‑loop control is critical in precision sports like archery, while open‑loop control underpins rapid, automatic actions in sprinting or tennis serves.

Feedback concepts such as knowledge of results (KR) and knowledge of performance (KP) directly inform coaching strategies. Sports psychologists emphasize KP because it provides athletes with actionable information about technique rather than just outcomes. This aligns with modern coaching practices that use video analysis and biomechanical feedback to enhance skill acquisition. The psychological impact of feedback—building confidence, reducing anxiety, and fostering autonomy—makes it a cornerstone of applied sports psychology.

Practice distribution and transfer of training also highlight the psychological side of motor learning. Distributed practice supports memory consolidation and reduces fatigue, while transfer principles explain how skills in one domain (e.g., balance training) can improve performance in another (e.g., gymnastics). Sports psychologists use these insights to structure training schedules that maximize learning efficiency and to anticipate both positive and negative transfer effects when athletes cross‑train or adopt new techniques.

Looking Forward

We’ve explored motor learning fundamentals: types of motor skills (discrete vs. continuous, open-loop vs. closed-loop), the critical role of knowledge of results & knowledge of performance in providing feedback for improvement, the superiority of distributed over massed practice, observational learning benefits, & transfer of training principles demonstrated through mirror tracing. In Part 2, we’ll explore sports psychology topics: how arousal levels affect performance through the Yerkes-Dodson Law, & how mental imagery enhances skill acquisition without physical practice.