Welcome to Doing Research! (OCR GCSE Psychology J203)
Welcome to one of the most important chapters in your GCSE Psychology course! Whether you are sitting Component 01 (where you will design your own investigation) or Component 02 (where you will evaluate a novel scenario), research methods make up a huge part of your final grade in Section D.
Psychologists do not just guess why people think, feel, and act the way they do — they carry out investigations. In this chapter, we will break down the six core research methods you need to master: Experiments, Interviews, Questionnaires, Observations, Case Studies, and Correlations.
Don't worry if this seems like a lot to learn at first! We will take each method step by step, look at everyday analogies, highlight key strengths and weaknesses (especially focusing on reliability and validity), and point out common exam traps so you can score top marks.
1. Experiments
An experiment is an investigation designed to discover if changing one thing causes a direct change in another. In psychological terms, an experiment tests a cause-and-effect relationship.
To understand experiments, you need to know three key terms:
• Independent Variable (IV): The variable that the researcher intentionally changes or manipulates (the "cause").
• Dependent Variable (DV): The variable that the researcher measures to see the effect of the IV (the "effect").
• Extraneous Variables: Any other unwanted variables that could accidentally affect the DV if not properly controlled.
Everyday Analogy: Think of baking a cake. If you want to test whether changing the amount of sugar (IV) makes the cake taste sweeter (DV), you must keep the oven temperature, baking time, and flour brand exactly the same (controlled extraneous variables).
A. Laboratory Experiments
Definition: An experiment conducted in a tightly controlled, artificial environment (like a university testing room or laboratory) where the researcher directly manipulates the IV and controls extraneous variables.
Strengths:
• High internal validity: Because extraneous variables are strictly controlled, researchers can be confident that changes in the DV were truly caused by the IV.
• High reliability: The procedure is highly standardised, meaning other researchers can easily repeat (replicate) the experiment to check if they get the same results.
Weaknesses:
• Low ecological validity / mundane realism: The artificial environment and tasks may feel unnatural, meaning participants might not behave as they would in real life.
• Demand characteristics: Participants might guess the aim of the study and change their behaviour to please the researcher or act unnaturally.
B. Field Experiments
Definition: An experiment carried out in a natural, real-world setting (like a school classroom, shopping centre, or workplace) where the researcher still directly manipulates the IV.
Strengths:
• Higher ecological validity: Because it happens in a real-world setting, participants display more natural behaviour.
• Fewer demand characteristics: If participants do not realise they are taking part in an experiment, their reactions are genuine.
Weaknesses:
• Lower internal validity: It is much harder to control extraneous variables in a busy, real-world environment (e.g. weather, background noise).
• Harder to replicate: Real-world conditions change constantly, making exact replication difficult.
C. Natural Experiments
Definition: An investigation where the researcher takes advantage of a naturally occurring change in the IV. The researcher does not manipulate the IV themselves.
Strengths:
• Ethical and practical: Allows psychologists to study things that would be unethical or impossible to set up artificially (such as the effects of a new government law or an institutional change).
• High ecological validity: The changes occur in real life, so behaviour is natural.
Weaknesses:
• No direct control over variables: Because the researcher cannot control who experiences the IV or what extraneous variables occur, establishing a definite cause-and-effect link is very difficult.
• Cannot be directly replicated: Natural events rarely happen in the exact same way twice.
Key Takeaway for Experiments: Lab experiments give you control (high reliability, high internal validity), while Field and Natural experiments give you realistic behaviour (high ecological validity) at the cost of control.
2. Interviews
An interview is a face-to-face or direct questioning method where a researcher asks participants questions verbally.
A. Structured Interviews
Definition: An interview where the questions are pre-written and fixed. The interviewer reads out the exact same questions in the exact same order to every participant, without adding new questions.
Strengths:
• High reliability: The standardised format makes it very easy to repeat with multiple participants and compare responses.
• Reduced interviewer bias: Because the interviewer sticks strictly to the script, their personal opinions are less likely to influence the participant.
Weaknesses:
• Inflexible: The interviewer cannot ask follow-up questions to explore surprising or interesting points made by the participant.
• Less detail: Answers tend to be brief and lack deep personal context.
B. Unstructured Interviews
Definition: A conversational interview with no fixed list of set questions. The researcher has broad topics to discuss, but questions are created dynamically based on what the participant says.
Strengths:
• Rich qualitative data: Provides in-depth, detailed insights into a person's thoughts, feelings, and underlying motives (high construct validity).
• Flexible: The interviewer can freely clarify questions and explore unexpected topics.
Weaknesses:
• Low reliability: Every interview is unique, making it nearly impossible for another researcher to replicate precisely.
• Difficult to analyse: Comparing open, conversational answers across different participants is time-consuming and subjective.
• Risk of interviewer bias: The interviewer might accidentally steer the conversation or interpret answers based on their own expectations.
Key Takeaway for Interviews: Structured interviews are rigid, easy to compare, and reliable. Unstructured interviews are flexible, rich in detail, but difficult to replicate.
3. Questionnaires (Surveys)
A questionnaire is a written self-report method where participants record their own answers to a set of pre-written questions on paper or online.
A. Open Questions
Definition: Questions that do not provide fixed response options, allowing participants to answer freely in their own words (e.g. "Describe how you feel when revising for an exam.").
• Data produced: Qualitative data (descriptive, word-based information).
• Strength: Gives rich detail and reveals the true depth of participant opinions.
• Weakness: Difficult and time-consuming to categorise, code, and analyse statistically.
B. Closed Questions
Definition: Questions with fixed options to choose from (e.g. Yes/No, tick boxes, or multiple choice).
• Data produced: Quantitative data (numerical information that can be counted).
• Strength: Easy to standardise, count, graph, and compare across large groups of people.
• Weakness: Lacks depth. Forcing people into preset boxes might not represent how they truly feel, lowering validity.
C. Rating Scales (e.g. Likert Scales)
Definition: A type of closed question where participants rate their level of agreement or feeling along a numerical or descriptive scale (e.g. 1 = Strongly Disagree to 5 = Strongly Agree).
• Strength: Turns subjective feelings and attitudes into numerical scores that can be averaged and compared statistically.
• Weakness: People can suffer from response sets (such as always picking the middle option out of laziness) or social desirability bias (answering how they think they "should" answer rather than being honest).
Key Takeaway for Questionnaires: Closed questions and rating scales give quantitative data that is easy to analyse; open questions give qualitative data that is full of detail.
4. Observations
An observation is a non-experimental research method where psychologists systematically watch and record what people or animals do. In OCR GCSE Psychology, observations are categorised into three distinct pairs:
Pair 1: Naturalistic vs. Controlled
• Naturalistic Observation: Watching behaviour in its everyday, real-world setting without interference (e.g. observing children playing in a school playground).
Strength: High ecological validity.
Weakness: Lack of control over extraneous factors.
• Controlled Observation: Watching behaviour inside a structured environment, such as a laboratory playroom with one-way mirrors.
Strength: High control over the environment and easier to replicate.
Weakness: The artificial setting might cause participants to act unnaturally.
Pair 2: Overt vs. Covert
• Overt Observation: Participants know they are being watched (e.g. an observer sitting in the room with a clipboard in plain sight).
Strength: Highly ethical because informed consent can be obtained.
Weakness: Participants may change their behaviour due to observer effects or demand characteristics.
• Covert Observation: Participants do not know they are being watched (e.g. hidden cameras or two-way mirrors).
Strength: Behaviour is completely natural and genuine.
Weakness: Raises serious ethical issues regarding lack of informed consent and invasion of privacy.
Pair 3: Participant vs. Non-Participant
• Participant Observation: The researcher actively joins in with the group being studied while observing.
Strength: Gives deep, first-hand insight into the group's dynamics.
Weakness: The researcher may lose objectivity ("go native") and become emotionally involved.
• Non-Participant Observation: The researcher remains separate from the group and watches from the outside.
Strength: The researcher remains objective and unbiased.
Weakness: The researcher might miss subtle meanings behind certain interactions.
Exam Warning: Do not confuse Covert with Non-Participant! A researcher can be Overt and Non-Participant (sitting openly in the corner of a room) or Covert and Participant (joining a club undercover without telling anyone).
5. Case Studies
Definition: An in-depth, comprehensive investigation of a single individual, small group, institution, or unique event, often conducted over a long period of time (longitudinal).
How data is collected: Case studies use a mixture of methods, combining both:
• Qualitative data: In-depth interviews, personal diaries, and direct observations.
• Quantitative data: Memory test scores, IQ tests, and biological measurements.
Strengths:
• Unique insight: Allows psychologists to investigate rare, unusual, or extreme situations that would be unethical to create experimentally (e.g. individuals with rare brain injuries or severe childhood isolation).
• Rich, detailed data: Provides a holistic and complete picture of human experience over time.
Weaknesses:
• Cannot be generalised (low population validity): Because the study focuses on one unique person or group, the findings cannot be applied to the wider population.
• Subjectivity: Researchers often build a close relationship with the participant, which can lead to biased interpretations.
• Cannot show cause and effect: There are no controlled baseline conditions to prove what caused specific behaviours.
Key Takeaway for Case Studies: Fantastic for studying rare phenomena in extreme detail, but you cannot generalise the results to other people!
6. Correlations
Definition: A non-experimental technique used to measure the strength and direction of a relationship (association) between two variables. In a correlation, these variables are called co-variables.
The Three Types of Correlation:
1. Positive Correlation: As one co-variable increases, the other co-variable also increases.
Example: As revision hours increase, exam test scores increase.
2. Negative Correlation: As one co-variable increases, the other co-variable decreases.
Example: As hours spent playing video games late at night increase, hours of sleep decrease.
3. Zero / No Correlation: There is no relationship between the two co-variables.
Example: Shoe size and intelligence score.
Strengths:
• Useful as a starting point to spot patterns or trends before setting up an experiment.
• Allows researchers to investigate relationships between variables that would be unethical to manipulate experimentally.
CRITICAL EXAM RULE: Correlation Does NOT Equal Causation!
A correlation shows that two variables are linked, but it does not prove that one variable causes the other.
Why? Because an unknown third variable (intervening variable) might be responsible for both.
Example: There is a strong positive correlation between ice cream sales and sunburn rates. Eating ice cream does not cause sunburn! Instead, hot sunny weather (the third variable) causes both ice cream sales and sunburn to rise.
Key Takeaway for Correlations: Always use the term co-variables (never IV/DV) and never write that a correlation "proves cause and effect"!
Common Pitfalls & Top Tips for the OCR J203 Exam
1. Contextualise Your Answers (Component 02, Section D)
OCR examiners frequently point out that students lose marks by writing generic textbook definitions. If an exam question asks: "Evaluate the use of a naturalistic observation in this study," do not just say "It has high ecological validity." You must link it to the scenario: "It has high ecological validity because the children were playing in their real school playground, so their sharing behaviour was natural."
2. Don't Mix Up "Reliability" and "Validity"
• Reliability = Consistency: Can the study be repeated to get the same results? (Standardised procedures, structured interviews, closed questions help reliability).
• Validity = Truth / Accuracy: Is the study measuring what it claims to measure? (Real-world settings, open questions, covert observations help validity by capturing genuine behaviour).
3. Language Checklist:
• In an Experiment: Use Independent Variable, Dependent Variable, and talk about cause-and-effect.
• In a Correlation: Use Co-variables, relationship / association, and never say cause-and-effect.
• In a Case Study: Never call the individual "the experimental sample".
Quick Summary Checklist
Before sitting your exam, make sure you can:
• Identify the 3 types of experiments (Lab, Field, Natural) and their trade-off between control and realism.
• Compare Structured vs. Unstructured interviews in terms of reliability and data depth.
• Distinguish between Open vs. Closed questionnaire questions and the types of data they produce (qualitative vs. quantitative).
• Correctly pair up observation terms (Naturalistic/Controlled, Overt/Covert, Participant/Non-Participant).
• Explain why case study findings cannot be generalised.
• Draw and explain Positive, Negative, and Zero correlations and explain why correlation is not causation.