CAIE AS Level Psychology (9990) - Methodology Syllabus Notes
Research Methods
1.1. Experiments
An experiment investigates a causal relationship by manipulating an independent variable (IV) and observing its effect on a dependent variable (DV).
Types of Experiments:
Laboratory Experiments:
Conducted in an artificial setting.
Strict controls are implemented.
Seeks to establish a causal relationship.
Strengths:
High standardization allows for easy replication to test reliability.
High control enhances confidence that the IV directly affects the DV.
Weaknesses:
Artificial environment lacks ecological validity.
Participants may exhibit demand characteristics.
Field Experiments:
Conducted in the participant's normal environment.
Researcher controls some variables, but it's difficult to control all.
Strengths:
Realistic setting provides high ecological validity.
Limited demand characteristics lead to more natural, valid behavior.
Weaknesses:
Difficult to control situational variables, making it hard to isolate the IV's effect on the DV.
Ethical issues may arise from participants not knowing they're part of a study.
Natural Experiments:
IV is naturally occurring and cannot be directly manipulated.
Studies the effect of an existing difference or change.
Not a true experiment because the IV is not manipulated.
Strengths:
High ecological validity due to the IV being naturally occurring.
Valid representation of behavior.
Weaknesses:
Difficult to establish causality between the IV and DV.
Difficult to replicate to test for reliability as the event is naturally occurring.
Experimental and Control Conditions:
Experimental Condition: One or more situations in an experiment that represent different levels of the IV and are compared.
Control Condition: A situation in which the IV is absent; used for comparison with the experimental condition(s).
1.2. Self-Reports
Self-reports involve gathering data directly from participants through questionnaires or interviews.
Questionnaires:
Written questions to gather information from participants.
Types of Questionnaires:
Likert Scales: Questions assessing the degree to which participants agree or disagree with something.
Rating Scales: Questions where participants provide answers on a numerical scale.
Open Questions: Allow for detailed, unrestricted answers.
Closed Questions: Offer a limited set of responses.
Strengths:
Participants are more likely to give truthful answers since it's not face-to-face.
Large samples can be surveyed quickly, enhancing representativeness and generalizability.
Weaknesses:
Participants may provide socially desirable answers.
Too many closed questions might force an answer that doesn't reflect the participant's true opinion.
Interviews:
Verbal questions asked directly to participants.
Types of Interviews:
Structured: Questions in a fixed order, often scripted and highly standardized.
Semi-structured: Fixed list of questions with the flexibility for follow-up questions.
Unstructured: Questions depend on the respondent’s answers; a list of topics may guide the interview.
Strengths:
Open questions enable participants to reveal reasons for their behavior or opinions.
Weaknesses:
Participants may be less truthful due to face-to-face interaction or social desirability.
1.3. Case Studies
In-depth investigation of a single instance (person, family, institution) that produces detailed data specific to that instance.
Strengths:
Researchers collect rich, in-depth data, enhancing the validity of findings.
High ecological validity as participants are studied in their everyday lives.
Weaknesses:
Findings might be difficult to generalize because the case is unique.
Attachments forming between the researcher and participant may reduce objectivity, affecting data analysis and validity.
1.4. Observations
Watching human or animal behavior.
Observer Roles:
Overt: Participants know they are being observed.
Covert: Participants are unaware of being observed.
Participant: Observer is part of the social setting.
Non-participant: Observer remains detached.
Observation Types:
Structured: Observer records a limited range of behaviors.
Unstructured: Observer records a range of behaviors, often used in pilot studies.
Naturalistic: Study conducted in the participants’ normal environment without interference.
Controlled: Study conducted in a manipulated environment.
General Strengths:
If participants are unaware, ecological validity increases.
Quantifiable data allows for statistical analysis with minimal bias.
General Weaknesses:
Aware participants may alter their behavior, reducing validity.
Naturalistic studies may be hard to replicate due to uncontrolled variables, reducing reliability.
Participant Observation:
Strengths:
High ecological validity.
Greater understanding of motives enhances validity.
Weaknesses:
Ethical problems concerning informed consent.
Observer's presence can alter group behavior, lowering validity.
Non-Participant Observation:
Strengths:
Participants' behavior is less affected.
Weaknesses:
Difficult to gather detailed qualitative data.
Structured Observation:
Strengths:
Behavioral checklists allow objective quantitative data collection and statistical analysis.
Weaknesses:
Restricted sampling of behaviors may not explain why they occur.
Unstructured Observation:
Strengths:
Generates rich qualitative data to explain behaviors.
Weaknesses:
Observers may focus on eye-catching behaviors and not represent all behaviors fully.
Naturalistic Observation:
Strengths:
Natural behavior due to unawareness of being watched.
High ecological validity.
Weaknesses:
Little control over extraneous variables makes it difficult to establish cause and effect.
Replication may be difficult due to the lack of a standardized procedure.
Controlled Observation:
Strengths:
Increased confidence in identifying causes of behavior.
Fewer extraneous variables.
Weaknesses:
Artificial settings can influence participant behavior.
Low ecological validity.
1.5. Correlations
Looks for a relationship between two measured variables without manipulation.
Cannot assume causation.
Types of Correlations:
Positive: Increase in one variable accompanies an increase in the other.
Negative: Increase in one variable accompanies a decrease in the other.
No Correlation: No apparent relationship between the variables.
Strengths:
Useful when experiments are unethical or impractical.
Weaknesses:
Cannot establish a cause-and-effect relationship due to potential third variables.
Restricted to quantitative research, limiting the ability to measure why behaviors occur.
1.6. Hypotheses and Aims
Aim: The purpose of the investigation, stating what the study intends to show.
Hypothesis: A testable statement predicting a difference or relationship.
Types of Hypotheses:
Alternative Hypothesis: Predicts the difference or relationship between variables.
Directional (One-tailed): Predicts the direction of the relationship.
Non-Directional (Two-tailed): Predicts that a relationship will exist, but not its direction.
Null Hypothesis: States that any difference or correlation in the results is due to chance.
1.7. Variables
Independent Variable (IV): Manipulated factor to create different conditions.
Dependent Variable (DV): Measured factor expected to change under the influence of the IV.
Operationalization: Defining variables for accurate manipulation, measurement, and replication.
1.8. Experimental Design
How participants are allocated to different levels of the IV.
Types:
Independent Measures Design: Different participants in each level of the IV.
Strengths:
Reduces the likelihood of participants guessing the study's aim, minimizing demand characteristics.
No order effects.
Weaknesses:
Participant variables can affect the DV.
Requires more participants.
Repeated Measures Design: Each participant performs in every level of the IV; uses counterbalancing (ABBA design).
Strengths:
Eliminates participant variables.
Requires fewer participants.
Weaknesses:
Higher chance of demand characteristics.
Order effects can reduce validity.
Matched Pairs Design: Participants are paired based on similar traits, and one member of each pair performs in a different level of the IV.
Strengths:
Controls for individual differences.
Suitable when repeated measures may not work due to order effects.
Weaknesses:
Time-consuming to match participants.
Difficult to match people exactly, which can affect internal and external validity.
1.9. Controlling of Variables
Essential for establishing certainty in study findings.
Extraneous Variable: Randomly affects the DV across all IV levels.
Confounding Variable: Systematically affects one level of the IV, obscuring its effect (situational or participant variables).
Control: Maintaining constant potential extraneous variables.
1.10. Types of Data
Qualitative Data: Descriptive, in-depth data.
Strengths:
Provides detailed accounts in participants' own words.
Allows understanding of why participants think, feel, or act a certain way.
Weaknesses:
Subjective interpretation.
Potential for researcher bias.
Quantitative Data: Numerical data.
Strengths:
Facilitates easier comparison and statistical analysis.
Objective and scientific.
Weaknesses:
Oversimplifies complex ideas and behaviors.
1.11. Sampling of Participants
Population: A group sharing characteristics from which a sample is drawn.
Sample: Group selected to represent the population.
Sampling Technique: Method to obtain participants.
Types:
Opportunity Sampling: Choosing participants available at the time and place.
Strengths:
Quick and easy, large numbers can be obtained.
Weaknesses:
Unlikely to gain a wide variety of participants, limiting generalizability.
Volunteer (Self-Selected) Sampling: Participants invited via advertisements or emails.
Strengths:
Lower drop-out rate.
Weaknesses:
Unlikely to gain a wide variety of participants, limiting generalizability.
Random Sampling: Each population member is assigned a number, and a fixed amount are chosen randomly.
Strengths:
Easier to generalize to the target population.
Weaknesses:
Difficult to obtain details necessary to draw the sample.
A perfectly representative sample cannot be guaranteed.
1.12. Validity
Extent to which a study tests what it claims to test.
Internal Validity: How well an experiment controls confounding variables.
Ecological Validity: Extent to which findings generalize to other situations.
Mundane Realism: Extent to which a task represents real-world situations.
Face Validity: Whether a measure appears to test what it claims to test.
Concurrent Validity: How well a test correlates with a previously validated measure.
Generalizability: How widely the findings apply to other settings and populations.
Demand Characteristics: Features that give away the aims, potentially altering participant behavior.
Objectivity: Unbiased viewpoint.
Subjectivity: Personal viewpoint, which can reduce validity.
1.13. Reliability
Consistency of a procedure, task, or measure.
Internal Reliability: Standardized procedures ensuring each participant experiences the same thing.
External Reliability: Extent to which results can be replicated.
Inter-rater/Inter-observer Reliability: Agreement between researchers interpreting qualitative data.
Methods to Test Reliability:
Split-Half Method: Compares results from the first and second halves of a test or questionnaire.
Test-Retest Method: Measures consistency by using the same test twice and comparing results.
1.14. Data Analysis
Measures of Central Tendency:
Mean: Average score; \frac{\sum{x}}{n}, where n is the number of scores.
Median: Middle score when data is ranked.
Mode: Most frequent score.
Measures of Spread:
Range: Difference between largest and smallest values + 1.
Standard Deviation: Average difference between each score and the mean.
Normal Distribution: Symmetrical spread about the mean, median, and mode, forming a bell curve.
Bar Charts: Graphs for discrete categories.
Histograms: Illustrate continuous data.
Scatter Graphs: Display data from correlational analysis.
Ethical Guidelines
2.1. Ethical Issues and Guidelines
Ethical Issues: Concerns about the welfare of participants.
Ethical Guidelines: Advice to consider participant welfare and wider society.
2.2. Ethical Guidelines in Relation to Human Participants
Based on British Psychological Society’s (BPS) Code of Human Research Ethics (2014).
Privacy: Avoid invasion of personal physical space.
Debriefing: Full explanation of aims and consequences at the end.
Protection: No greater risk than in daily life.
Informed Consent: Participants should know enough to decide to participate.
Right to Withdraw: Participants can remove themselves and their data at any time.
Deception: Avoid misinformation; minimize risk and debrief thoroughly if unavoidable.
Confidentiality: Keep results and information safe.
2.3. Ethical Guidelines in Relation to Animal Participants
Based on British Psychological Society’s guidelines (2012).
Replacement: Consider alternatives like videos.
Species and Strain: Choose ethically and scientifically suitable species.
Numbers: Use the smallest number of animals possible.
Procedures: Enrich rather than harm.
Pain and Distress: Avoid causing pain or distress; monitor and act on adverse effects.
Housing: Avoid isolation and crowding; recreate natural environments.
Reward, Deprivation, and Aversive Stimuli: Consider normal habits and requirements; ensure no alternative motivation exists.
Anaesthesia, Analgesia, and Euthanasia: Protect from pain during surgery; euthanize if suffering lasting pain.
Issues and Debates
3.1. The Application of Psychology to Everyday Life
Practical use of theories or findings to improve processes or lives.
Strengths:
Can be used to improve human behavior.
Weaknesses:
Studies might be unethical to gain more valid results.
Studies need to be high in ecological validity to be of more use to society, but this can be quite difficult if they are conducted in a laboratory experiments.
3.2. Individual and Situational Explanations
Extent to which behavior results from unique individual factors or setting factors.
Strengths:
Understanding which behaviors are influenced by individual vs situational factors helps explain human behavior.
If it is an interaction, then that is useful too.
Weaknesses:
It is not always easy to separate individual and situational factors.
Studies might be unethical in order to gain more valid results.
Studies need high ecological validity to be of more use to this debate, but this can be difficult if it is a laboratory experiment.
3.3. Nature Versus Nurture
Nature: Behavior from innate, genetic factors.
Nurture: Behavior from environmental influences.
Strengths:
Understanding which behaviors are influenced by nature vs. nurture help explain human behaviour more clearly.
If it is an interaction, then that is useful too.
Weaknesses:
It is not always easy to separate out what is nature and what is nurture.
If behaviour is seen to be purely down to nature (genetics) this can be very socially sensitive.
Studies might be unethical in order to gain more valid results.
3.4. The Use of Children in Psychological Research
Giving consent is important for children under 16 & a risk assessment must take place.
Refer to Ethical guidelines for human participants
3.5. The Use of Animals in Psychological Research
Refer to Ethical guidelines for animal participants