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examBoard: AQA
examType: GCSE
lessonTitle: Allocation to Conditions
When psychologists conduct experiments, they need to decide how to assign participants to different experimental conditions. This process is called allocation to conditions and it's a crucial part of designing a fair test. The way we allocate participants can have a big impact on the validity of our results.
Key Definitions:
Imagine you're testing whether a new revision technique helps students remember more information. If you put all the clever students in one group and all the struggling students in another, any difference in test scores might be due to the students' abilities rather than your revision technique. That's why how you allocate participants to conditions is so important!
In medical research, poor allocation methods have sometimes led to incorrect conclusions about whether treatments work. This is why modern clinical trials use careful allocation methods to ensure fair testing of new medicines.
There are three main methods psychologists use to allocate participants to conditions:
Participants are assigned to conditions by chance, like flipping a coin or using a random number generator.
Participants are matched on important characteristics, then one from each pair goes into each condition.
Each participant takes part in all conditions, serving as their own control.
Random allocation (also called randomisation) means that each participant has an equal chance of being placed in any of the experimental conditions. This helps to spread individual differences evenly across conditions.
In medical and psychological research, the "gold standard" is the randomised control trial (RCT). For example, when testing a new therapy for depression, researchers randomly allocate participants to either receive the new therapy or a standard treatment. This helps ensure that any differences in recovery rates are due to the therapy itself, not to differences between the people in each group.
In a matched pairs design, participants are first matched on important characteristics (like age, gender, or test scores) and then one member of each pair is randomly allocated to each condition.
How to match participants: Researchers might use pre-tests, questionnaires, or existing data to match participants. For example, in a study on teaching methods, students might be matched based on their previous exam scores before being allocated to different teaching groups.
In a study testing whether background music helps memory, researchers matched participants based on their scores on a preliminary memory test. From each matched pair, one person was randomly assigned to study with music and the other to study in silence. This helped ensure that any differences in memory performance weren't just due to some people naturally having better memories than others.
In a repeated measures design (also called within-subjects design), each participant takes part in all experimental conditions. This means participants serve as their own controls.
Controlling for order effects: To reduce order effects in repeated measures designs, researchers use counterbalancing. This means changing the order of conditions for different participants so that order effects are spread evenly.
The famous Stroop test measures how long it takes to name the ink colour of words. Participants typically do both conditions: naming colours when the word matches the ink colour (e.g., "RED" written in red ink) and when it doesn't match (e.g., "RED" written in blue ink). Using a repeated measures design means that differences in reaction time are more likely due to the experimental manipulation rather than some participants being naturally faster readers than others.
When deciding which allocation method to use, researchers need to consider several factors:
Best when you have a large sample size and want to create equivalent groups without extensive pre-testing. For example, testing whether a new teaching method improves exam scores across many students.
Best when you have a smaller sample and know which participant characteristics might affect results. For example, matching participants on IQ scores when testing problem-solving strategies.
Best when you have very few participants available or when individual differences are likely to be large. For example, testing how different types of music affect the same person's concentration levels.
No allocation method is perfect! Each has strengths and weaknesses and the best choice depends on your specific research question and practical constraints.
Allocation to conditions is a crucial part of experimental design in psychology. The three main methods random allocation, matched pairs and repeated measures each have their own advantages and disadvantages. The choice of method can significantly impact the validity of research findings. By understanding these different approaches, you can better evaluate psychological research and understand why researchers make the design choices they do.
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