Experimental research in psychology
Key Concepts in Experimental Design
Participant Assignment
Experimental Group: Receives an experimental procedure that is different.
Control Group: Receives standard procedures for comparison.
Assessments done on the differences in another variable between groups.
Types of Experimental Design
1. Unrelated Design (Between-Subjects)
Different participants assigned to different conditions.
Example: Comparing memory test errors in participants listening to loud music vs. white noise.
2. Related Design (Within-Subjects)
Same participants exposed to multiple conditions.
Example: Memory test errors when music is played vs. no music.
Reasons for Using Experimental Design
Essential for utilizing specialized equipment (e.g., EEG).
Controls variables, minimizing distractions (e.g., noise, lighting).
Allows clearer causal conclusions than non-experimental designs.
Common in fields like cognitive and social psychology (e.g., learning, memory).
Alternative Explanations in Research
Limitations of Non-Experimental Design
Lacks control over variables; does not clarify cause/effect relationships.
Heat Causes Aggression? Example
Non-Experimental: Observed honking frequency.
Experimental: Control over temperature while evaluating aggressive responses.
True Experiment Elements
Random participant assignment to conditions.
Manipulation of the independent variable.
Standardization of procedures for consistency.
Experimental Manipulation
Independent and Dependent Variables
Independent Variable: The manipulated factor causing changes.
Dependent Variable: Measured effects/results.
Know independent variable levels beforehand.
Dependent variable values reveal the impact of the independent variable post-manipulation.
Example: Alcohol consumption impacting cognitive errors.
Experimental Control and Standardization
Conditions must be identical except for the manipulated variable.
All factors controlled: instructions, environment, participant characteristics.
Random Assignment and its Importance
Equalizes participant characteristics and reduces bias.
Goal: To prevent systematic differences in treatment allocation.
Bias and Variability in Research
Confounding variables obscure results by varying with the independent variable.
Differences between groups result in unreliable conclusions.
Matching Participants
Control differences through participant pairing based on key variables that impact the study (e.g., age, gender).
Pre-existing Differences
Include a pre-test to assess baseline differences before the experimental manipulation.
Helps in understanding the impact of experimental conditions.
Limitations of Pre-tests
Risk of sensitization; potentially alters participant behavior.
Solutions: Insert unrelated tasks between pre- and post-tests or increase time between testing.
Within-Subjects Design
Reduces participant differences by using the same individuals across all conditions.
Order Effects: Address potential biases through counterbalancing and careful design.
Advanced Experimental Designs
Can include multiple independent variables, increasing complexity and interaction understanding.
Use more than one dependent variable for a comprehensive analysis of effects.
Issues in Experimental Design
Placebo Effect
Participants experience improvement from placebo treatments believing they receive active treatments.
Experimenter and Demand Characteristics
The experimenter's behavior and expectations can unintentionally affect results.
Participants may change behavior based on their understanding of the experiment's aims.
Conclusion
Experimental designs are critical for establishing cause-effect relationships but must be carefully controlled to avoid biases and inaccuracies.