Component 2: Experimental design (knowledge, understanding and evaluation of) — Eduqas A-Level Psychology
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Experimental design in Eduqas A-Level Psychology covers the key decisions researchers make when planning studies: choosing experimental designs (independent measures, repeated measures, matched pairs), controlling extraneous and confounding variables, allocating participants to conditions, and selecting appropriate experimental designs to test hypotheses. Understanding these choices is essential for evaluating validity, reliability and the strength of causal conclusions drawn from psychological research.
Component 2: Experimental design (knowledge, understanding and evaluation of) explained
Component 2: Experimental design (knowledge, understanding and evaluation of) covers 3 specification points, including independent groups and repeated measures.
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Open a point below for its explanation and revision guidance.
independent groups
Independent groups is a design in which each participant takes part in only one condition of the independent variable. The researcher recruits one pool of participants, then allocates each person to the experimental condition or the control condition so that no one appears in both. Allocation may be random, for example by drawing names, which spreads individual differences across the two groups. Because each person contributes a single score, the two sets of results come from different people, so the design avoids order effects and demand characteristics that arise from doing both conditions. The cost is that participant variables such as age, mood or ability may differ between groups and act as confounding variables, and more participants are needed overall.
repeated measures
Repeated measures is a design in which every participant takes part in all conditions of the independent variable, so each person produces a score in each condition. The researcher compares each participant's performance across conditions, which controls participant variables because the same individuals are compared with themselves. A concrete case: every volunteer learns one word list in silence and a different word list with music playing, and the researcher compares each person's two recall scores. The main weakness is order effects, since practice, fatigue or boredom from the first condition can influence the second. Researchers reduce this by counterbalancing, splitting participants so that half do the conditions in one order and half in the reverse order. Repeated measures also need fewer participants but risk demand characteristics because people experience both conditions.
matched pairs
Matched pairs is an independent-measures design in which the researcher pairs each participant with another who is similar on a relevant variable, then allocates one member of each pair to each condition. For example, in a study of a revision technique, learners are paired on prior test score, then one of each pair uses the technique and the other does not. Because different people take part in each condition, order effects are avoided, but the design depends on the researcher identifying and measuring a genuinely relevant matching variable. It is not the same as repeated measures, where the same person does both conditions, nor random allocation, where pairing plays no part.
Your focus
- Define independent groups as a design where each participant completes one condition only
- Explain how random allocation is used to reduce the influence of participant variables
- Evaluate independent groups by identifying at least one strength and one limitation
Show all 9 objectives
- Define repeated measures as a design where each participant completes every condition
- Explain how counterbalancing reduces order effects in repeated measures
- Evaluate repeated measures by identifying at least one strength and one limitation
- Define matched pairs as an independent-measures design using paired participants.
- Explain how a relevant matching variable is used to allocate participants to conditions.
- Evaluate matched pairs by weighing reduced participant variables against the difficulty of effective matching.
Which command word is this?
Give reasons or mechanisms. In Eduqas Psychology, 'explain' requires you to state a point and then justify it with a cause-effect link, for example explaining why counterbalancing reduces order effects.
Component 2: Experimental design (knowledge, understanding and evaluation of) exam tips
Topic Overview
Experimental design is the set of decisions a researcher makes about how participants are allocated to conditions and how variables are controlled. In Eduqas A-Level Psychology, you must know the three main designs (independent measures, repeated measures, matched pairs), their strengths and limitations, and how they affect validity and reliability. You also need to understand how to control extraneous and confounding variables through standardisation, random allocation, counterbalancing and matching.
This topic matters because the quality of an experiment depends on its design. A poorly designed study cannot support causal conclusions, no matter how interesting the hypothesis. Experimental design connects to research methods, data analysis and the evaluation of classic studies across all psychology topics, so examiners frequently test it in both short-answer and extended-response questions.
Key Concepts
- →Independent measures design: different participants in each condition; avoids order effects but risks participant variables.
- →Repeated measures design: same participants in all conditions; controls participant variables but risks order effects and demand characteristics.
- →Matched pairs design: participants matched on key variables and allocated to different conditions; reduces participant variables and order effects but matching is imperfect and time-consuming.
- →Extraneous variables: unwanted variables that may affect the dependent variable if not controlled; confounding variables systematically vary with the independent variable and undermine causal conclusions.
- →Control techniques: random allocation, counterbalancing, standardisation, single-blind and double-blind procedures, and matched pairs.
Marking Points
- Identifies that each participant experiences only one level of the independent variable
- States that different participants form the separate conditions or groups
- Explains that random allocation can distribute participant variables across conditions
- Recognises that independent groups avoid order effects because no one repeats the task
- Notes that participant variables may still confound results because groups contain different people
- States that independent groups require more participants than repeated measures
- Identifies that each participant takes part in every condition of the independent variable
- States that the same participants are compared across conditions
- Explains that participant variables are controlled because individuals act as their own comparison
- Recognises that order effects such as practice or fatigue can influence later conditions
- Describes counterbalancing as a method of reducing order effects by varying the order of conditions
- Notes that repeated measures require fewer participants than independent groups
- Identifies matched pairs as an independent-measures design in which different participants take part in each condition.
- Explains that participants are paired on a variable relevant to the dependent variable before one member of each pair is allocated to each condition.
- States that matched pairs reduces participant variables compared with independent measures without creating order effects.
- Recognises that the design depends on the researcher choosing and measuring a suitable matching variable, which may be difficult or imperfect.
- Distinguishes matched pairs from repeated measures and from random allocation of unpaired participants.
Examiner Tips
- 💡Define the design precisely before evaluating it, so the definition earns the knowledge mark and the evaluation earns the analysis mark
- 💡Link each strength or weakness to a named effect, such as order effects or participant variables, rather than offering a bare label
- 💡Use a short applied example with two separate groups to show you can recognise the design in a scenario
- 💡State clearly that the same participants complete every condition, because this distinguishes repeated measures from independent groups
- 💡Name the specific order effect, such as practice or fatigue, when evaluating the design
- 💡Explain counterbalancing as varying the order of conditions between participants rather than repeating the same order
- 💡Name the design and state that different participants are used in each condition before adding any evaluation.
- 💡Give a concrete matching variable linked to the dependent variable to show understanding rather than reciting a definition.
- 💡When comparing designs, contrast matched pairs with repeated measures on order effects and with independent measures on participant variables.
- 💡Always name the experimental design explicitly and then link each strength or limitation to validity, reliability or causal conclusions. Generic answers without a link rarely gain full marks.
- 💡When asked to improve a study, suggest a specific design change (for example, 'use a matched pairs design and match on age and baseline reaction time') rather than vague advice like 'control the variables better'.
- 💡Use precise terminology: participant variables, order effects, counterbalancing, standardisation, demand characteristics, internal validity. Examiners reward correct technical language.
Common Mistakes
- Claims that the same participants complete both conditions; correct this by stating that each person takes part in one condition only
- Asserts that independent groups eliminate all participant variables; correct this by explaining that random allocation only reduces their influence
- Confuses independent groups with independent variables; correct this by distinguishing the design from the variable being manipulated
- States that independent groups remove the need for a control condition; correct this by explaining that separate groups can still include a control group
- Claims that different participants complete each condition; correct this by stating that every participant completes all conditions
- Asserts that repeated measures remove all order effects; correct this by explaining that counterbalancing only balances their influence across participants
- Describes counterbalancing as giving every participant the same order; correct this by explaining that the order is varied between participants
- States that repeated measures increase the number of participants needed; correct this by explaining that fewer participants are required
- Confuses matched pairs with repeated measures; keep the point that different participants serve in each condition.
- Treats matched pairs as random allocation with no pairing; state that participants are deliberately paired on a relevant variable first.
- Assumes matching removes all participant variables; note that it only reduces the influence of the variable chosen for matching.
- Describes matched pairs as a sampling method; classify it as an experimental design instead.
- Students often think repeated measures is always better because it uses the same participants. In fact, repeated measures introduces order effects and demand characteristics, so counterbalancing is essential and the design is not automatically superior.
- Students sometimes say that random allocation removes all extraneous variables. Random allocation only balances participant variables across conditions on average; it does not control situational variables, so standardisation is still needed.
- Students confuse extraneous and confounding variables. Extraneous variables add noise; confounding variables change systematically with the IV and make it impossible to isolate the cause of the effect.
Revision Plan
- 1Day 1-2: Create a comparison table of independent measures, repeated measures and matched pairs designs, listing one strength and one limitation for each with a concrete example.
- 2Day 3-4: Learn definitions and examples of extraneous and confounding variables, and make a list of control techniques with a specific example of each.
- 3Day 5-6: Practise applying designs to novel scenarios. For each scenario, identify the design, suggest one improvement and explain the effect on validity.
- 4Day 7-8: Complete past-paper questions on experimental design, focusing on 4- and 6-mark questions. Mark your answers against the mark scheme and rewrite any that lost marks.
- 5Day 9-10: Use active recall and spaced practice to memorise key terms and evaluate at least two classic studies in terms of their experimental design.
Exam Question Types
- 📋Short-answer definition questions (2-3 marks): Define independent measures, repeated measures or matched pairs, and give one strength or limitation. Advice: be precise and use an example.
- 📋Application questions (4-6 marks): Read a scenario and identify the design, explain one strength and one limitation, or suggest an improvement. Advice: always link your point back to the scenario and to validity.
- 📋Evaluation questions (6-8 marks): Discuss the strengths and limitations of a named design or compare two designs. Advice: use a balanced structure with clear topic sentences and psychological terminology.
- 📋Design-a-study questions (6-10 marks): Outline how you would design an experiment to test a hypothesis, including design, controls and participant allocation. Advice: cover design, variables, controls, sampling and ethics briefly but accurately.
Command Word Expectations (EDUQAS)
Give reasons or mechanisms. In Eduqas Psychology, 'explain' requires you to state a point and then justify it with a cause-effect link, for example explaining why counterbalancing reduces order effects.
Weigh strengths and limitations and reach a justified conclusion. You must use psychological terminology, refer to validity or reliability, and make a judgement rather than just listing points.
Give a clear, accurate account of what something is or how it is done. No evaluation is needed, but detail and correct terminology are required for full marks.
How Students Lose Marks (Examiner Pitfalls)
Step-by-Step Worked Solutions
Question: A psychologist wants to test whether drinking caffeine improves reaction time. She recruits 30 participants and randomly assigns 15 to a caffeine condition and 15 to a decaffeinated condition. Reaction time is measured in milliseconds. Identify the experimental design used and explain one strength and one limitation of this design in this study. (6 marks)
- 1.Step 1: Identify the design. The psychologist uses different participants in each condition (15 in caffeine, 15 in decaffeinated), so this is an independent measures design.
- 2.Step 2: State one strength. Because different participants are used, there are no order effects such as practice or fatigue, and participants cannot guess the aim from experiencing both conditions, so demand characteristics are reduced.
- 3.Step 3: State one limitation. Participant variables such as natural reaction time, age or caffeine tolerance may differ between groups, creating confounding variables that reduce internal validity. Random allocation helps but does not guarantee equivalence.
- 4.Step 4: Link to the study. The difference in reaction time could be due to pre-existing differences rather than caffeine, so caution is needed before concluding cause and effect.
Question: A researcher investigates whether background music affects memory recall. Each participant learns a word list in silence and then a different word list with music playing. The order of conditions is counterbalanced. Explain why counterbalancing was used and outline one remaining limitation of this design. (4 marks)
- 1.Step 1: Identify the design. The same participants take part in both conditions (silence and music), so this is a repeated measures design.
- 2.Step 2: Explain counterbalancing. Counterbalancing means half the participants do silence first then music, and the other half do music first then silence. This controls for order effects such as practice, fatigue or boredom, which could otherwise confound the results.
- 3.Step 3: State a remaining limitation. Even with counterbalancing, demand characteristics may still occur because participants experience both conditions and may guess the hypothesis, changing their behaviour. Also, the two word lists must be equivalent in difficulty, which is difficult to guarantee.
- 4.Step 4: Link to validity. If participants guess the aim or if lists differ in difficulty, the internal validity of the memory recall measure is threatened.