Research methods — AQA GCSE Psychology
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Research methods explained
Research methods covers the scientific processes, design, and analysis of psychological research.
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It includes the formulation of hypotheses, selection of sampling methods, experimental design, various research methods (experiments, observations, interviews, questionnaires, case studies), correlation, ethical considerations, and data handling/statistical analysis.
What to demonstrate
- Formulation of null and alternative hypotheses
- Identification of independent, dependent, and extraneous variables
- Application of sampling methods (random, opportunity, systematic, stratified)
Show all 10 objectives
- Evaluation of experimental designs (independent groups, repeated measures, matched pairs)
- Distinction between laboratory, field, and natural experiments
- Understanding of qualitative vs quantitative and primary vs secondary data
- Calculation and interpretation of descriptive statistics (mean, median, mode, range)
- Construction and interpretation of data displays (frequency tables, bar charts, histograms, scatter diagrams)
- Knowledge of BPS ethical guidelines and ways to manage ethical issues
- Understanding of reliability and validity in research design
Research methods exam tips
Topic Overview
Research methods is the backbone of psychology, covering how psychologists design studies, collect data, and draw conclusions. In AQA GCSE Psychology, this topic is essential because it equips you with the skills to evaluate studies and understand how psychological knowledge is built. You'll learn about experiments, observations, self-report techniques, correlations, and ethical considerations — all of which are tested in Paper 1 and Paper 2.
Why does this matter? Because every psychological theory you study — from memory to social influence — is based on research. By understanding research methods, you can critically assess whether a study's findings are valid, reliable, and applicable. This topic also develops your analytical thinking, which is valuable beyond exams, such as in evaluating news articles or scientific claims.
In the wider subject, research methods links to all other topics. For example, when studying 'Memory', you'll need to know how experiments like Baddeley's (1966) were conducted. Mastery of this topic helps you answer 'evaluate' and 'discuss' questions, which are common in higher-mark questions. It also prepares you for the 'Research Methods' section of the exam, which is worth around 25% of the total marks.
Key Concepts
- →Hypotheses: directional (predicts the direction of difference) vs. non-directional (predicts a difference but not the direction). Operationalised variables are clearly defined so they can be measured.
- →Experimental designs: independent groups (different participants in each condition), repeated measures (same participants in all conditions), and matched pairs (participants matched on key variables then split). Each has strengths and weaknesses regarding order effects, participant variables, and demand characteristics.
- →Sampling methods: random, systematic, stratified, opportunity, and volunteer. You need to know how each works and its bias/representativeness. For example, opportunity sampling is quick but often biased.
- →Ethical guidelines: informed consent, deception, debriefing, right to withdraw, confidentiality, and protection from harm. The BPS (British Psychological Society) sets these. You must know how to apply them to a study.
- →Types of data: quantitative (numerical, easy to analyse) vs. qualitative (words, rich detail but harder to summarise). Primary data is collected first-hand; secondary data is from existing sources.
Marking Points
- Formulation of null and alternative hypotheses
- Identification of independent, dependent, and extraneous variables
- Application of sampling methods (random, opportunity, systematic, stratified)
- Evaluation of experimental designs (independent groups, repeated measures, matched pairs)
- Distinction between laboratory, field, and natural experiments
- Understanding of qualitative vs quantitative and primary vs secondary data
- Calculation and interpretation of descriptive statistics (mean, median, mode, range)
- Construction and interpretation of data displays (frequency tables, bar charts, histograms, scatter diagrams)
- Knowledge of BPS ethical guidelines and ways to manage ethical issues
- Understanding of reliability and validity in research design
Examiner Tips
- 💡Use scenario-based questions to practice applying research methods knowledge to novel situations
- 💡Ensure you can justify the choice of a specific research method or design based on its strengths and weaknesses
- 💡Practice constructing and labeling graphs accurately, including axes and titles
- 💡Memorize the BPS ethical guidelines and be prepared to suggest how to deal with specific ethical issues in a given study
- 💡Ensure you are comfortable with the mathematical requirements, including decimal/standard form and percentages
- 💡Always operationalise your variables in exam answers. For example, instead of saying 'memory', say 'the number of words correctly recalled from a list of 20'. This shows precision and gains marks.
- 💡When evaluating a study, use the GRAVE structure: Generalisability (sample), Reliability (replicability), Application (real-world use), Validity (does it measure what it claims?), and Ethics. This ensures you cover key points.
- 💡For the 9-mark 'design a study' question, plan your answer: state the aim, hypothesis (directional or non-directional), method (experiment, observation, etc.), sample, procedure, controls (e.g., standardised instructions), and ethical considerations. Use bullet points or paragraphs — either is fine as long as it's clear.
Common Mistakes
- Confusing independent and dependent variables
- Failing to identify appropriate control methods for extraneous variables
- Misinterpreting scatter diagrams or correlational relationships
- Incorrectly applying sampling methods to specific scenarios
- Confusing the purpose of different experimental designs
- Inaccurate calculation of descriptive statistics or failure to use appropriate significant figures
- Misconception: A correlation proves causation. Correction: Correlation only shows a relationship between two variables; it does not mean one causes the other. There could be a third variable (extraneous) causing both.
- Misconception: A pilot study is the same as the main study. Correction: A pilot study is a small-scale trial run to check for problems (e.g., unclear instructions, timing issues) before the actual study. It helps improve the procedure.
- Misconception: The independent variable (IV) is what you measure; the dependent variable (DV) is what you change. Correction: The IV is manipulated by the researcher; the DV is measured to see the effect of the IV. For example, in a memory experiment, the IV might be the type of music (silent vs. loud), and the DV is the number of words recalled.
Frequently Asked Questions
What is the difference between a lab experiment and a field experiment?
A lab experiment takes place in a controlled environment (e.g., a psychology lab) where the researcher manipulates the IV and controls extraneous variables. This increases internal validity but may lack realism. A field experiment occurs in a natural setting (e.g., a school or street), so behaviour is more natural, but there is less control over extraneous variables, which can reduce validity. Both are types of experiments with an IV and DV.
How do I know whether to use a directional or non-directional hypothesis?
Use a directional (one-tailed) hypothesis when previous research suggests a clear direction of the results (e.g., 'Participants who revise for 2 hours will recall more words than those who revise for 30 minutes'). Use a non-directional (two-tailed) hypothesis when there is no previous research or the findings are conflicting (e.g., 'There will be a difference in word recall between participants who revise for 2 hours and those who revise for 30 minutes').
What are demand characteristics and how can they be reduced?
Demand characteristics are cues in a study that lead participants to guess the aim and change their behaviour (e.g., trying to please the researcher or act unnaturally). They can be reduced by using a single-blind design (participants don't know the condition), deception (with ethical approval), or naturalistic observations where participants are unaware they're being studied.
Why is random sampling not always the best method?
Random sampling gives every member of the target population an equal chance of being selected, which reduces bias and increases representativeness. However, it can be difficult and time-consuming to achieve, especially with large populations. Also, even if you randomly select, you might end up with an unrepresentative sample by chance (e.g., all females). Practical constraints often lead researchers to use opportunity or volunteer sampling instead.
What is the difference between reliability and validity?
Reliability refers to consistency — if a study is repeated, will you get the same results? It can be assessed using test-retest (same test twice) or split-half methods. Validity refers to whether the study measures what it claims to measure. Internal validity is about the design (e.g., controlling extraneous variables), while external validity is about generalising to real life. A study can be reliable but not valid (e.g., a poorly designed test that gives consistent but wrong results).
How do I answer a 'design a study' question in the exam?
First, identify the aim from the question. Write a clear, operationalised hypothesis (directional or non-directional). Choose an appropriate method (e.g., lab experiment, observation). Describe the sample (size, target population, sampling method). Outline the procedure step-by-step, including how you will manipulate the IV and measure the DV. Mention controls (e.g., standardised instructions, random allocation). Finally, address ethical considerations (e.g., informed consent, debriefing). Keep it concise but detailed.