1.1.3 Experimental Research

PSYC 224 Handy Cognitive Psychology: Introduction & Methods

Overview of Experimental Research

Key Components of Experimental Research:

  • Independent Variable (IV): The factor that is intentionally manipulated by the researcher to observe its effect. This is the presumed cause in the experimental framework.

  • Dependent Variable (DV): The factor that is measured and is expected to change when the IV is manipulated. This represents the effect in the cause-and-effect relationship.

  • Confounding Variables: Additional factors that, if not controlled or accounted for, may influence the outcomes of the experiment, leading to erroneous conclusions. Proper experimental design aims to minimize the impact of these variables to ensure the reliability of the results.

Types of Variables in Experimentation

Subjects:

  • Who: Comparison is made across different individuals. This can include various parameters such as:

    • Age: Understanding age-related differences in cognitive processing.

    • Experience: Considering how prior knowledge or exposure affects performance in experiments.

Materials:

  • What: Comparison of different types of stimuli used in experiments, which can encompass:

    • Modality: Sensory channels through which stimuli are presented (e.g., visual, auditory).

    • Characteristics: Specific features of the stimuli, such as color, size, or complexity.

Experimental Contexts:

  • How: Comparison among various tasks, instructions, and environmental settings affecting performance. This could include the setting of the experiment (laboratory vs. natural environment) and instructions given to subjects.

Example Experiment: Pennies and Luck

Experiment Insight:

  • Title: "LIBERTY LIBERTY LIBERTY 1243 1243 1943"

  • Hypothesis: The act of picking up a penny can influence feelings of luck, subsequently enhancing academic performance during exams.

Findings of the Experiment

  • Results Summary: Students who picked up pennies before taking an exam scored, on average, significantly higher than those who did not engage in this behavior. This suggests a possible causal relationship between the psychological act of picking up a penny and improved academic results.

Causal Interpretation and Headline Results

  • Strong Statements:

    • Picking up pennies correlates with an increase in exam grades.

    • Suggestion: "Want a higher grade? Pick up a penny on the way to an exam!" This humorous recommendation implies that the superstition surrounding pennies may indeed have some validity.

Interpretation of Results

  • Results indicate a correlation but caution against hastily concluding causation without meticulous control of other influencing factors. To attribute a change in grades directly to the act of picking up a penny, other external variables need to be systematically controlled.

Investigating Underlying Mechanisms

  • Potential Mechanisms:

    • Increased mood or confidence stemming from the act of picking up a penny, leading to better focus and performance in academic settings.

Experimental Design Adjustments:

  • Divide students into two belief groups about luck (believers vs. non-believers in superstitions). This creates a second IV: Belief in luck.

Analysis of Average Scores

  • Results Summary:

  • Students who picked up a penny (PUP) achieved a 75% average score versus the 65% average score from those who did not. This highlights the main effect of the independent variable (penny picking) on performance.

Belief as an Independent Variable

  • Scores Based on Belief:

    • Believers in Luck: 70% average score.

    • Non-believers in Luck: 70% average score.

  • No significant main effect of belief was found in this instance, but interactions between belief and performance must also be analyzed.

Exploring Interactions in Data

Main Effects Summary:

  • Picking up a penny provides a notable increase in average exam scores (75% PUP vs. 65% NoPUP).

  • Interaction Hypothesis: If belief in luck does not affect outcomes, one would expect consistent subgroup scores across believers and non-believers.

Interaction of Variables

Data Summary:

  • Believers:

    • PUP: 80% average score.

    • No-PUP: 60% average score.

  • Non-believers:

    • PUP: 70% average score.

    • No-PUP: 70% average score.

  • Total Scores: The data reveals distinct patterns that indicate performance is dependent on the subjects' belief in luck.

Visualization of Interaction Effects

  • Graphical Representation:

  • Comparing average scores between the believers and non-believers, conditioned on whether they picked up a penny, elucidates that the effect of this behavior is inextricably linked to individual belief statuses.

Conclusions and Further Research Directions

  • The observed interactions suggest that psychological variables, such as happiness and confidence, may play a more crucial role than mere luck in determining success.

  • Future studies could evaluate direct measures of ‘luck’ by analyzing whether the act of penny picking correlates with success in luck-based activities such as gambling, providing further insights into the psychology of luck and superstition.