Welcome to Planning Psychological Research!
Have you ever wondered how psychologists turn a curious question—like "Does drinking coffee improve memory?"—into a scientific, rigorous experiment? In this chapter, you will learn the exact toolkit psychologists use to plan their studies from start to finish.
Planning research is one of the most important topics in your OCR GCSE (9–1) Psychology course. It appears across both exam papers: in Component 01 (where you have to design your own investigation) and in Component 02 (where you evaluate unfamiliar research studies). Don't worry if all the terminology feels overwhelming at first—we will break down every single concept step-by-step with clear examples!
1. Hypotheses: Making Testable Predictions
Before carrying out an investigation, a researcher must write a hypothesis. A hypothesis is simply a precise, testable prediction about what will happen in a study.
The Two Main Types of Hypotheses
• Null Hypothesis (\(H_0\)): This predicts that there will be no significant difference between conditions or no relationship between variables. Any small difference observed is purely down to chance.
Example: "There will be no significant difference in the number of words recalled between participants who drink coffee and those who drink water; any difference is due to chance."
• Alternative Hypothesis (\(H_1\)): This predicts that there will be a significant difference or relationship between variables.
Directional vs. Non-Directional Hypotheses
When writing an alternative hypothesis (\(H_1\)), you must decide whether to make it directional or non-directional:
1. Directional Hypothesis (One-tailed): Predicts the exact direction of the results (e.g., using words like faster, slower, more, less, higher, lower).
Example: "Participants who drink 200ml of caffeinated coffee will recall significantly more words from a list of 20 than participants who drink 200ml of water."
2. Non-Directional Hypothesis (Two-tailed): Predicts that an effect or difference will happen, but does not state which group will do better or worse (using words like a difference).
Example: "There will be a significant difference in the number of words recalled from a list of 20 between participants who drink 200ml of caffeinated coffee and participants who drink 200ml of water."
Top Exam Tip: Operationalising Your Hypothesis
In the exam, you will lose marks if your hypothesis is too vague! To get full marks, your hypothesis must be fully operationalised. This means you must clearly state both conditions of the Independent Variable (IV) and the exact measurement unit of the Dependent Variable (DV).
• Weak (0-1 marks): "Coffee makes memory better."
• Full Marks: "Participants who consume 200ml of coffee will recall a significantly higher number of words out of 20 on a memory test compared to participants who consume 200ml of water."
Key Takeaway: The Null Hypothesis (\(H_0\)) always predicts no difference, while the Alternative Hypothesis (\(H_1\)) predicts a difference. Directional hypotheses state which way the results will go, while non-directional hypotheses simply state there will be a difference.
2. Variables: What We Change, Measure, and Control
A variable is anything that can vary or change within an investigation.
Independent vs. Dependent Variables
• Independent Variable (IV): The variable that the experimenter directly manipulates, alters, or changes to see its effect.
• Dependent Variable (DV): The variable that is measured by the researcher to assess the effect of the IV.
Memory Trick: The Independent variable is what I (the researcher) change. The Dependent variable is the Data collected!
Operationalisation
Operationalisation means defining variables in precise, measurable, and objective terms so that another researcher can replicate the exact study.
Everyday Analogy: If a recipe says "bake for a while in a hot oven", it is not operationalised. If it says "bake at 180°C for 25 minutes", it is operationalised!
Extraneous vs. Confounding Variables
• Extraneous Variables (EVs): Any unwanted, extra variables other than the IV that could influence the DV if they are not controlled.
- Participant Variables: Individual traits of the participants (e.g., age, natural memory ability, intelligence, tiredness).
- Situational Variables: Features of the testing environment (e.g., background noise, lighting, room temperature, time of day).
• Confounding Variables: An extraneous variable that was not controlled and has systematically changed alongside the IV, directly ruining the results. When a confounding variable is present, you cannot be sure whether the IV or the confounding variable caused the change in the DV.
Control Techniques
Psychologists use several clever techniques to stop extraneous variables from interfering:
• Standardisation: Keeping all procedures, instructions, timings, and environmental conditions identical for every single participant.
• Randomisation / Random Allocation: Putting participants into experimental conditions entirely by chance (e.g., drawing names out of a hat or using a random number generator) so individual differences are evenly spread between groups.
• Single-Blind Procedure: The participants do not know which condition of the study they are in. This prevents demand characteristics (when participants guess the aim and change their behaviour).
• Double-Blind Procedure: Neither the participants nor the researcher interacting with them knows which condition the participants are in. This controls both demand characteristics and investigator effects (researcher bias).
Key Takeaway: We manipulate the IV, measure the DV, and control Extraneous Variables so they do not turn into Confounding Variables!
3. Experimental Designs
An experimental design describes how participants are organised across the different conditions of the Independent Variable.
1. Independent Measures Design (Independent Groups)
• How it works: Different participants are used in each condition of the IV (e.g., Group A drinks coffee; Group B drinks water).
• Strength: No order effects (participants cannot get tired or practice the task) and lower risk of demand characteristics because participants only see one condition.
• Weakness: Participant variables (individual differences between the two groups, like natural intelligence) can act as an extraneous variable; also requires twice as many participants.
2. Repeated Measures Design
• How it works: The same group of participants takes part in all conditions of the study (e.g., all participants complete the test with water on Monday, then repeat the test with coffee on Tuesday).
• Strength: Eliminates participant variables because the exact same people are in both conditions; requires fewer participants overall.
• Weakness: High risk of order effects—participants might perform better on the second test due to practice, or worse due to boredom or fatigue.
• How to control order effects: Psychologists use counterbalancing (\(AB/BA\) design). Half the participants do Condition A followed by Condition B, while the other half do Condition B followed by Condition A. This balances out practice or fatigue effects evenly across both conditions.
3. Matched Pairs Design
• How it works: Different participants are used in each condition, but they are pre-tested and matched in pairs on key characteristics (e.g., matching two people of the same age and IQ). One member of the pair is placed in Condition 1, and the other is placed in Condition 2.
• Strength: Greatly reduces participant variables while completely avoiding order effects (since each person is only tested once).
• Weakness: Very time-consuming and difficult to match people perfectly. If one person drops out, the data for their entire pair is lost!
Common Examiner Pitfall to Avoid
Do not confuse experimental designs with research methods! If an exam question asks for an "experimental design", you must write Independent Measures, Repeated Measures, or Matched Pairs—not "experiment" or "observation".
Key Takeaway: Independent Measures uses different people per group (risking participant variables), Repeated Measures uses the same people (risking order effects—fixed by counterbalancing), and Matched Pairs pairs similar people together.
4. Populations and Sampling
Psychologists usually want to find out how large groups of people behave, but they cannot test everyone in the world!
Key Terms
• Target Population: The entire group of people the researcher wants to study and draw conclusions about (e.g., "all GCSE students in the UK").
• Sample: The smaller group of participants selected from the target population who actually take part in the research.
• Representativeness and Generalisability: If a sample mirrors the characteristics, ages, and backgrounds of the target population accurately, it is representative. This allows the researcher to generalise (apply) their findings to the wider target population.
The Three Sampling Methods in OCR GCSE Psychology
1. Random Sampling
• How it is done: Every single member of the target population has an equal chance of being selected (e.g., pulling names out of a hat containing the whole school register or using a computer random number generator).
• Strength: Highly representative and free from researcher bias.
• Weakness: Very time-consuming; requires a complete list of everyone in the target population, and selected people may refuse to take part.
2. Opportunity Sampling
• How it is done: Selecting individuals who are available and willing to take part at the time and place of the study (e.g., asking people walking past in a school hallway or shopping centre).
• Strength: Very quick, convenient, and cheap to carry out.
• Weakness: High risk of bias and unrepresentative, as it leaves out anyone who is not present at that specific time and location.
3. Self-Selected (Volunteer) Sampling
• How it is done: Participants volunteer themselves in response to an advert, poster, email, or flyer.
• Strength: Easy to organise; participants are willing, motivated, and less likely to drop out.
• Weakness: Volunteer bias—people who volunteer for studies tend to share specific traits (e.g., more helpful, more confident, or have extra free time), making the sample unrepresentative.
Common Examiner Pitfall: Sample Size vs. Representativeness
Examiners frequently point out that a large opportunity sample is not automatically representative! Testing 500 students in one single school cafeteria is still an opportunity sample and cannot be generalised to all UK teenagers because it excludes everyone outside that specific school.
Key Takeaway: Random sampling gives everyone an equal chance and reduces bias; Opportunity sampling is fast but biased; Volunteer sampling relies on willing participants who may share specific unrepresentative traits.
5. Ethics and the BPS Code of Conduct
Psychologists in the UK must follow strict rules set by the British Psychological Society (BPS) to protect the safety, dignity, and rights of all participants.
The 6 Key Ethical Guidelines & How to Deal with Them
1. Informed Consent
• The Issue: Participants must agree to take part with full knowledge of the aim, risks, and procedures.
• How to deal with it: Participants sign a written consent form before the study begins. If participants are under 16 years old, parental or guardian consent must be obtained.
2. Deception
• The Issue: Deliberately misleading participants or withholding the true aim of the research.
• How to deal with it: Deception should only occur if scientifically necessary to avoid demand characteristics. It must be addressed immediately afterwards in a comprehensive debrief.
3. Protection from Physical and Psychological Harm
• The Issue: Participants must not experience greater physical harm, stress, embarrassment, or mental distress than they would in everyday life.
• How to deal with it: The researcher must stop the experiment immediately if distress is observed, and offer post-study support or counselling if needed.
4. Right to Withdraw
• The Issue: Participants must feel completely free to leave the study at any point without penalty.
• How to deal with it: Participants are explicitly told at the start, middle, and end that they can leave at any time and can have their data deleted from the study even after it has finished.
5. Confidentiality and Anonymity
• The Issue: Personal details and individual test scores must be kept strictly private by law.
• How to deal with it: Use participant numbers, letters, or pseudonyms (fake names) instead of real names, and keep all data securely stored.
6. Debriefing
• The Issue: Ensuring participants leave the study in the same psychological state they entered.
• How to deal with it: A post-experimental discussion where the researcher reveals the true aims of the study, answers questions, addresses any deception, and checks participant wellbeing.
Top Exam Tip for Ethics Questions
Avoid informal everyday phrases like "just say sorry" or "ask if it's okay". Always use official psychological terminology: obtain written informed consent, provide a full debrief, maintain confidentiality through anonymised participant numbers, and remind participants of their right to withdraw.
Key Takeaway: The BPS guidelines protect participants through Informed Consent, Deception controls, Protection from Harm, Right to Withdraw, Confidentiality, and a thorough Debrief.
Quick Summary Checklist
Before sitting your exam, make sure you can:
• Write a fully operationalised Null (\(H_0\)), Directional, and Non-Directional hypothesis.
• Identify the IV and DV from a novel research scenario.
• Explain the difference between extraneous and confounding variables.
• Evaluate the 3 experimental designs (Independent Measures, Repeated Measures, Matched Pairs) and explain counterbalancing.
• Compare Random, Opportunity, and Volunteer sampling methods.
• Identify BPS ethical issues and explain the correct procedures to resolve them.