Measuring Performance in Psychology: Methods and Error Analysis

Measuring Performance

Introduction

Understanding how to measure performance is essential in psychology, especially in fields such as motor learning, cognitive psychology, and neuropsychology. This topic covers the distinction between performance and learning, methods for assessing performance, and processes for measuring error.

Performance vs. Learning

Definitions and Distinctions

• Performance: An observable behaviour or action, such as hitting a ball. It is what can be directly measured or seen during a task.

• Learning: A relatively permanent change or improvement in performance as a result of practice or experience. Learning is inferred from changes in performance over time.

• Key Point: Performance can fluctuate due to temporary factors (e.g., fatigue, motivation), while learning reflects enduring capability.

• Example: A person may perform well in a single session (performance), but consistent improvement over multiple sessions indicates learning.

Methods for Measuring Performance

Performance Production Measures

Production measures focus on the behaviour required to achieve a goal.

• Definition: Measurement of the actions or processes involved in performing a task.

• Example: In archery, drawing the bow and releasing the arrow are production measures.

Performance Outcome Measures

Outcome measures focus on the result or goal achieved by the performance.

• Definition: Measurement of the success or result of the performance.

• Example: In archery, the accuracy of the shot on the target is an outcome measure.

Assessing Production

Methods for Assessing Production

• Human Judgement: Observers rate or describe the quality of movement. Useful for simple tasks but limited for complex or high-speed actions.

• Video Recording (Film, Digital): Allows for detailed analysis by slowing down movements and reducing observer bias. Common in sports and rehabilitation.

• High-Speed Filming and Computer Analysis: Enables calculation of position, velocity, and acceleration of body parts for precise movement analysis.

• Electromyogram (EMG): Measures electrical activity of muscles, allowing analysis of the size and timing of muscle contractions during movement.

• Brain Activity Measures:

  • EEG (Electroencephalogram): Records electrical activity ('brain waves') using electrodes on the scalp. Useful for studying timing and patterns of neural activity.

  • fMRI (Functional Magnetic Resonance Imaging): Measures blood flow to active brain areas, indicating which regions are involved during specific tasks.

Assessing Outcome

Outcome Measures

• Response Magnitude: Refers to the absolute size of the response. Examples include:

  • Number of laps run during track practice

  • Speed of puck shot by a player

  • Hours spent learning to drive

• Reaction Time (RT): Time from appearance of stimulus to beginning of movement.

• Fractionated Reaction Time:

  • Premotor Time (PRMOT): Time from stimulus until first EMG activity.

  • Motor Time (MOT): Time from first EMG activity until movement begins.

Measuring Error in Performance

Types of Error Measures  

Error measures are used to quantify accuracy and consistency in performance, especially in tasks requiring precision.

• Constant Error (CE):

  • Definition: Measures accuracy by considering the difference between each score and the target, including direction (positive or negative).

  • Formula: $CE = \frac{\sum (X_i - T)}{n}$

  • Example: For scores 10, 4, -1, -5 cm (target = 0 cm): $CE = \frac{10 + 4 - 1 - 5}{4} = 2$ cm

  • Interpretation: Average distance from criterion, showing both magnitude and direction of error.

• Variable Error (VE):

  • Definition: Standard deviation of scores, indicating variability or consistency around the mean.

  • Formula: $VE = \sqrt{\frac{\sum (X_i - \bar{X})^2}{n}}$

  • Example: For scores 10, 4, -1, -5 cm (mean = 2 cm): $VE = 5.6$ cm

  • Interpretation: Reflects inconsistency in movement relative to one's own average performance.

• Total Variability (Root Mean Square Error, RMS):

  • Definition: Overall error relative to the target, calculated as the root mean square of the differences.

  • Formula: $RMS = \sqrt{\frac{\sum (X_i - T)^2}{n}}$

  • Example: For scores 10, 4, -1, -5 cm (target = 0 cm): $RMS = 5.96$ cm

  • Interpretation: Spread of scores about the target; overall measure of success in achieving the target.

• Absolute Error (AE):

  • Definition: Mean of the absolute differences between scores and the target, ignoring direction.

  • Formula: $AE = \frac{\sum |X_i - T|}{n}$

  • Example: For scores 10, 4, -1, -5 cm (target = 0 cm): $AE = 5$ cm

  • Interpretation: Overall accuracy of performance, regardless of direction.

Summary Table: Error Measures

Measure	Formula	Interpretation
Constant Error (CE)	$CE = \frac{\sum (X_i - T)}{n}$	Average distance and direction from target
Variable Error (VE)	$VE = \sqrt{\frac{\sum (X_i - \bar{X})^2}{n}}$	Consistency/variability around mean
Total Variability (RMS)	$RMS = \sqrt{\frac{\sum (X_i - T)^2}{n}}$	Overall error relative to target
Absolute Error (AE)	$AE = \frac{\sum |X_i - T|}{n}$	Overall accuracy (ignores direction)

Applications and Importance

Why Measure Performance and Error?

• Helps in evaluating skill acquisition and learning in psychological research and applied settings (e.g., sports, rehabilitation).

• Provides objective data for comparing interventions, training methods, or individual differences.

• Supports understanding of underlying processes in motor control and cognitive function.

Conclusion

Measuring performance and error is fundamental in psychology for assessing behaviour, learning, and the effectiveness of interventions. By using both production and outcome measures, and analyzing different types of error, researchers and practitioners can gain a comprehensive understanding of skill development and performance quality.