psych 3100

Selection Optimization and Compensation Theory

  • Discussion on selection, optimization, and compensation theory through examples

  • Three main components:

    • Selection: Choosing a goal

    • Optimization: Working towards that goal

    • Compensation: Creating strategies or means to achieve that goal as needed

  • Examples of selection types:

    • Elective Selection: Choosing a desirable goal (e.g., becoming a professional basketball player)

    • Loss-Based Selection: Adjusting goals after facing a loss (e.g., an injury preventing someone from pursuing their goal)

  • Encouragement to review examples from class for better understanding.

Scientific Method and Research Basics

  • Importance of systematic knowledge and shared experience in research:

    • Individual experiences vary, necessitating objective methods.

    • Aim for unbiased and falsifiable research plans.

  • Generalizability: Research outcomes should apply beyond a specific group (e.g., generalizing findings from a small group of students to larger populations).

Levels Driving Research

  • Theory: Broadest level, aiming to explain phenomena based on prior observations or research.

    • Example: Albert Bandura's social learning theory, which explains behavior through the observation of others.

  • Research Question: More specific question the research study attempts to answer (e.g., "Does viewing violent media increase aggression?").

  • Hypothesis: A testable statement based on the theory (e.g., "People who consume violent media are more likely to exhibit aggressive behavior").

Types of Research Designs

  • Quantitative vs. Qualitative Distinction:

    • Quantitative Research: Focuses on numerical data and statistical analysis (e.g., surveys, experiments).

    • Qualitative Research: Focuses on non-numerical data, narratives, and understanding individual perspectives (e.g., interviews, focus groups).

Research Design Categories

  • Descriptive Research:

    • Aims to describe phenomena (e.g., "What percentage of teens report texting while driving?").

  • Correlational Research:

    • Measures relationships between variables without manipulation (e.g., relationship between book ownership and vocabulary).

  • Experimental Research:

    • Tests causal relationships through manipulation of independent variables (e.g., determining if increased reading time leads to higher vocabulary).

Correlations

  • Strength and Direction of Correlations:

    • Positive Correlation: Both variables increase or decrease together (e.g., increased alcohol consumption and depression symptoms).

    • Negative Correlation: One variable increases while the other decreases (e.g., increased alcohol consumption and lower GPA).

    • Strength measured by Pearson's correlation coefficient (r) ranging from -1 to 1.

    • Closer to -1 or 1 indicates stronger correlation.

    • A result near zero indicates weak or no correlation.

Types of Research Designs

  • Cross-Sectional Research:

    • Observing a sample at a single point in time (e.g., surveying high school students once).

    • Issues: Cohort differences may bias results (e.g., varying social media usage among different age groups).

  • Longitudinal Research:

    • Involves repeated observations of the same group over time (e.g., surveying students across several grades).

    • Advantages: Ability to observe changes and developments over time but suffer from attrition and practice effects.

  • Sequential Research:

    • Combines cross-sectional and longitudinal designs, comparing different cohorts over time (e.g., surveying students from different grades repeatedly).

    • Efficient and reduces the impact of cohort differences by allowing for comparisons across different age bands and times.

Examples of Research Designs

  • Cross-Sectional: Analyzes survey responses from each student in a high school.

  • Longitudinal: Surveys first-grade students and tracks them for four years.

  • Sequential: Surveys students across multiple grades, continuously gathering data until they complete the K-12 system.

Correlation Examples

  • Positive Correlation Example: More hours spent studying correspond to higher academic performance.

  • Negative Correlation Example: More hours playing video games correlating with lower GPA.

Discussion on Research Reliability and Bias

  • Challenges in researching sensitive topics (e.g., self-reported alcohol use) and how biases can affect data collection.

  • Ways to mitigate biases:

    • Use alternative reporting methods (e.g., peer reports) or immediate reporting surveys.

    • Recognize that consistency in response to survey instruments may change over time, impacting the reliability of longitudinal data.

Conclusion

  • Understanding these concepts is imperative for conducting, analyzing, and evaluating research effectively in both qualitative and quantitative domains.

  • Equally important is recognizing the implications of cohort effects in research design and interpretation.