Methodology in Psychology (CAIE AS Level Psychology 9990)
1. Research Methods
1.1 Experiments
Definition: An experiment is an investigation that seeks to identify a causal relationship where an independent variable (IV) is manipulated to observe effects on a dependent variable (DV).
Types of Experiments:
- Laboratory Experiments: Conducted in a controlled environment where the researcher can manipulate the IV and maintain strict control over the study settings. High reliability due to standardized conditions but may lack ecological validity.
- Field Experiments: Conducted in a natural setting for participants. The researcher can control some variables, but external variables can affect the DV, leading to challenges in determining causality.
- Natural Experiments: Researchers observe the effects of an IV that cannot be manipulated directly; the IV is predetermined by natural circumstances. This type lacks rigorous control over the IV and may be difficult to replicate.
Conditions in Experiments:
- Experimental Condition: Situations involving the presence of the IV.
- Control Condition: Situations without the IV, serving as a comparison.
1.2 Self-Reports
Definition: Involves participants providing information about themselves, primarily through questionnaires or interviews.
Types of Questionnaires:
- Likert Scales: Assess attitudes by asking participants to indicate their level of agreement or disagreement with statements.
- Rating Scales: Participants provide responses along a numeric scale.
- Open Questions: Allow detailed, unrestricted answers from participants.
- Closed Questions: Offer limited, predefined responses for participants.
Types of Interviews:
- Structured: Pre-determined questions asked in a fixed order, promoting standardization.
- Semi-Structured: Fixed questions with room for additional questions based on responses.
- Unstructured: Flexible interviewing where the flow is controlled by participant responses.
1.3 Strengths and Weaknesses of Self-Reports
Questionnaires:
- Strengths:
- Anonymity may lead to more truthful responses.
- Can be disseminated to large samples quickly.
- Weaknesses:
- Risk of socially desirable responses.
Interviews:
- Strengths:
- In-depth data that provides insight into participant motivations.
- Weaknesses:
- Potential for bias affecting honest responses.
1.4 Case Studies
Definition: In-depth examination of a single instance (such as an individual, family, or institution) that yields rich qualitative data specific to that case.
1.5 Observations
Definition: A method involving watching and recording behaviors of individuals or groups. Observers can choose to be either overt (participants are aware) or covert (participants are unaware).
- Types:
- Participant Observers: Researchers immerse themselves in the group.
- Non-Participant Observers: Researchers observe without direct involvement in the group.
- Structured Observations: Limited behaviors are recorded; enhances focus and consistency.
- Unstructured Observations: Greater range of behaviors documented; flexibility in response to situations.
- Naturalistic vs. Controlled Observations:
- Naturalistic: Conducted in the participant's everyday environment without interference.
- Controlled: Conducted in a manipulated environment to study specific behaviors under set conditions.
1.6 Correlations
Definition: A statistical technique that evaluates the relationship between two variables, examining how changes in one may correspond to changes in another.
Types of Correlations:
- Positive Correlation: An increase in one variable accompanies an increase in another.
- Negative Correlation: An increase in one variable corresponds to a decrease in another.
- No Correlation: No expected relationship between the variables.
1.7 Hypotheses and Aims
Aim: Describes the purpose of the investigation without predicting outcomes.
Hypothesis: A testable prediction of a relationship/difference between variables.
- Types of Hypotheses:
- Directional (One-tailed): Predicts the direction of the relationship.
- Non-directional (Two-tailed): Predicts a relationship without specifying the direction.
- Null Hypothesis: States that observed effects are due to chance.
1.8 Variables
Independent Variable (IV): The factor manipulated to observe effects on the DV.
Dependent Variable (DV): The factor measured in response to changes in the IV.
Operationalization: Clearly defining variables so that they can be measured and tested consistently.
1.9 Experimental Design
Types:
- Independent Measures Design: Different participants are used for each level of the IV.
- Repeated Measures Design: The same participants are used across all levels of the IV; issues like order effects must be managed, potentially through counterbalancing.
- Matched Pairs Design: Pairs of participants are matched based on key variables; each pair experiences different IV levels.
1.10 Controlling of Variables
Extraneous Variables: Variables that can interfere with the DV; controlling these ensures the IV is the agent of change.
Situational Variables: External factors within the environment that may affect participants' behavior; control is crucial for consistency.
Participant Variables: Individual differences among participants can confound results and should be managed by randomization or matching.
1.11 Types of Data
Qualitative Data: Descriptive data that provides depth of understanding regarding psychological characteristics.
Quantitative Data: Numerical data that allows for significant statistical analysis.
1.12 Sampling of Participants
Population vs. Sample: The population is a broad group sharing characteristics; a sample is a selected subset of that population for study.
Sampling Techniques:
- Opportunity Sampling: Uses those readily available at the time of the study.
- Voluntary Sampling: Selects participants who choose to take part, often through advertisements.
- Random Sampling: Assigns numbers to the population and randomly selects participants, helping ensure representativeness.
1.13 Validity
Definition: The degree to which a study tests what it intends to.
- Internal Validity: Measures how well confounding variables are controlled.
- External/Ecological Validity: Refers to how findings generalize beyond the study situation.
- Face Validity: Perceived adequacy of a measure to its intended characteristic.
- Concurrent Validity: Comparison with an established measurement's results.
- Demand Characteristics: Participant behavior may change if they suspect the study's purpose, affecting validity.
1.14 Reliability
Definition: Consistency of a measure over time and across various conditions.
- Types:
- Internal Reliability: Consistency in the measure across different items.
- External Reliability: Consistency of results when replicated.
- Inter-rater Reliability: Agreement between different observers.
- Methods to Test:
- Split-half Method: Comparing results from two halves of a measure.
- Test-retest Method: Consistency of results across two separate testing events.
1.15 Data Analysis
Measures of Central Tendency: Identifies typical scores in a dataset.
- Mean: Average of scores.
- Median: Middle score after ranking.
- Mode: Most frequent score.
Measures of Spread: Describes variability in data.
- Range: Difference between max and min scores.
- Standard Deviation: Average deviation of scores from the mean.
Normal Distribution: A symmetrical distribution forming a bell curve; mean, median, and mode are equal.
Graphical Representations:
- Bar Charts: Represent discrete data.
- Histograms: Show continuous data.