Chapter 10: Introduction to Simple Experiments

Key Topics

• Introduction to simple experiments
• Examples of simple experiments
• Aspects of experimental design and methodology
• Validity and causal claims

Examples of Simple Experiments

1. Note-Taking Methods and Test Scores

• Researchers: Pam Mueller and Daniel Oppenheimer (2014)
• Participants: 67 college students
• Methods: Students took notes using laptops or handwritten notes while watching TED Talks
• Results: Both groups scored equally on factual questions; the handwritten group scored higher on conceptual questions
• Manipulated Variable: Method of note-taking (laptops vs. handwritten)
• Conclusion: Method of note-taking affects conceptual understanding

2. Serving Bowl Size and Portion Sizes

• Researchers: Researchers at Cornell University (2012)
• Participants: Participants served themselves pasta from either large or medium bowls
• Results: Participants took more pasta and consumed more calories from the large bowl
• Manipulated Variable: Size of the serving bowl (large vs. medium)
• Conclusion: Serving bowl size influences portion size and caloric intake

Experimental Variables

• Manipulated Variable: Researcher assigns participants to a particular level (e.g., note-taking method)
• Measured Variable: Researcher records outcomes (e.g., test scores, amount of pasta consumed)
• Independent Variable (IV): Manipulated by researcher (e.g., note-taking method)
• Dependent Variable (DV): Measured by researcher, depends on IV (e.g., test scores)
• Control Variable: Held constant (e.g., type of pasta)

Causal Claims

• Three Criteria:
  1. Covariance: Cause variable related to effect variable (e.g., serving bowl size and calories consumed)
  2. Temporal Precedence: Cause variable occurs before effect variable
  3. Internal Validity: Rule out alternative explanations

Experimental Design Methods

Independent Group Designs (Between-Subjects)

• Post-Test Only: Participants tested on the DV after exposure to IV
• Pre-Test/Post-Test: Participants tested on the DV before and after exposure to IV
• Example: Mindfulness training study
• Advantages: Random assignment can control selection effects
• Disadvantages: Participants might get full or exhausted

Within Group Designs (Within-Subjects)

• Repeated Measures Design: Same participants experience all levels of IV
• Concurrent Measures Design: Participants exposed to all levels of IV simultaneously
• Advantages:
  • Participants serve as their own controls
  • Increased statistical power
  • Fewer participants needed
• Disadvantages:
  • Order effects
  • May not be practical (e.g., teaching methods)
  • Potential for demand characteristics
• Counterbalancing: Mitigates order effects by varying the order of conditions

Validities in Experiments

Construct Validity

• Evaluates how well variables are operationalized and measured
• Example: Factual and conceptual questions in note-taking study

External Validity

• Generalization of results to other populations or settings
• Example: Note-taking study on college students may not generalize to middle school students

Statistical Validity

• Checks if the differences are statistically significant
• Measures effect size (e.g., Cohen's d)

Internal Validity

• Ensures no design confounds or selection effects
• Example: Random assignment in note-taking study controlled for selection effects

Summary

• Discussed examples of simple experiments
• Explained types of variables (independent, dependent, control)
• Covered criteria for causal claims (covariance, temporal precedence, internal validity)
• Compared experimental design methods (independent vs. within group designs)
• Explained how to interrogate causal claims using the four validities (construct, external, statistical, internal)