Variables and operationalisation | AQA A-Level Psychology Revision
- Revision Notes
- Aug 4
- 16 min read
Updated: Aug 23
For 7182 specification, first teach in September 2025
AQA A-Level Psychology | Free Revision Notes
Estimated study time: 50 minutes
Variables are the features of an investigation that researchers change, measure or control. This Variables and operationalisation A-Level Psychology revision page explains independent, dependent and extraneous variables, how variables are manipulated and controlled, and how abstract ideas can be turned into precise measurements. These skills are central to designing, interpreting and evaluating psychological research. The AQA specification requires students to understand the manipulation and control of variables, including independent, dependent and extraneous variables, as well as their operationalisation.
Learning Objectives 🎯
By the end of this revision page, you should be able to:
Define independent, dependent and extraneous variables.
Identify variables in unfamiliar research scenarios.
Explain how an independent variable is manipulated.
Explain why researchers control extraneous variables.
Operationalise independent and dependent variables precisely.
Suggest appropriate controls for variables that could affect an investigation.
Revision Notes 📚
What is a variable?
A variable is any feature that can change or take different values within an investigation.
Psychologists study variables to investigate patterns in behaviour and mental processes. In an experiment, the researcher usually changes one variable and measures whether this produces a change in another.
The three main types of variable covered in this lesson are:
Independent variable
Dependent variable
Extraneous variable
Researchers must identify these variables clearly when planning an investigation. This follows naturally from stating the purpose and predicted outcome of a study.
Independent variables
The independent variable, often shortened to IV, is the variable that is changed or selected so that its effect can be investigated.
In many experiments, the researcher manipulates the independent variable by creating two or more conditions.
For example, a researcher investigates whether background music affects memory:
Condition one: participants learn words in silence.
Condition two: participants learn words while music is playing.
The independent variable is the presence or absence of background music.
The IV must contain at least two conditions that can be compared. If every participant experienced exactly the same situation, the researcher would have no comparison through which to investigate the IV’s effect.
Manipulating the independent variable
Manipulation means deliberately changing the independent variable between conditions.
A researcher should manipulate the IV so that:
The conditions are clearly different.
The difference can be described precisely.
Other aspects of the procedure remain as consistent as possible.
The manipulation directly relates to the research aim.
Consider the following aim:
To investigate whether the presence of a mobile phone affects performance on a concentration task.
The IV could be manipulated as follows:
Condition | Manipulation of the independent variable |
Phone-present condition | A mobile phone is placed on the desk beside the participant |
Phone-absent condition | No mobile phone is placed on the desk |
The researcher has created two clearly defined conditions that differ in the presence of the phone.
Independent variables in different experiments
The way the IV is produced depends on the type of experiment.
Laboratory and field experiments
In laboratory and field experiments, the researcher manipulates the IV by creating different conditions.
For example:
Bright lighting compared with dim lighting.
Written instructions compared with spoken instructions.
Completing a task alone compared with completing it in a group.
Natural experiments
In a natural experiment, the change in the IV occurs naturally rather than being directly created by the researcher.
The researcher identifies groups or situations that already differ and compares their effects.
Quasi-experiments
In a quasi-experiment, the IV is based on a difference that already exists between people. The researcher does not manipulate this characteristic.
These distinctions are explored in laboratory, field, natural and quasi-experiments.
Dependent variables
The dependent variable, often shortened to DV, is the variable that is measured.
Researchers measure the DV to determine whether it changes when the IV changes. It is described as dependent because its value may depend on the condition of the independent variable.
In the background-music investigation:
IV: whether words are learned in silence or with music.
DV: memory performance.
However, “memory performance” is not yet sufficiently precise. The researcher must explain exactly how it will be measured.
It could be operationalised as:
The number of words correctly recalled from a list of 20 words during a two-minute recall period.
This definition allows the researcher to produce a numerical score for each participant.
Identifying the independent and dependent variables
A useful way to identify variables is to ask two questions:
What is being changed or compared?
This is usually the independent variable.
What outcome is being measured?
This is usually the dependent variable.
Example
A psychologist investigates whether completing a task in a quiet room or a noisy room affects the number of errors made.
What is being changed? The level of environmental noise.
What is being measured? The number of errors.
Therefore:
IV: whether the task is completed in a quiet or noisy room.
DV: the number of errors made on the task.
Independent and dependent variables in research aims
A well-written experimental aim usually includes both the IV and the DV.
For example:
To investigate whether studying with or without background music affects the number of words correctly recalled.
In this aim:
IV: studying with or without background music.
DV: the number of words correctly recalled.
This is much clearer than:
To investigate music and memory.
The second aim does not state what aspect of music will vary or how memory will be measured.
Extraneous variables
An extraneous variable is any variable other than the independent variable that could affect the dependent variable.
Extraneous variables matter because they provide possible alternative explanations for the results.
Suppose a researcher investigates whether music affects memory. Participants in the music condition complete the task in the morning, while participants in the silent condition complete it at the end of the day.
Time of day could affect participants’ alertness and memory scores. It is therefore an extraneous variable.
If the music group performs better, the researcher cannot be certain whether this was due to the music or the time at which the participants were tested.
Examples of extraneous variables
Extraneous variables may arise from the environment, the participants, the materials or the researcher’s procedure.
Possible examples include:
Noise outside the testing room.
Differences in room temperature or lighting.
Different instructions being given to different participants.
Variations in the time allowed to complete a task.
Differences in the difficulty of research materials.
Interruptions during one condition.
Differences in participants’ relevant abilities or experience.
The researcher offering more encouragement in one condition.
Equipment working differently between conditions.
Participants completing conditions in different circumstances.
A factor is only an extraneous variable if it could reasonably influence the dependent variable in that particular investigation.
Scenario: identifying extraneous variables
A psychologist investigates whether handwritten or typed revision notes lead to better test performance.
Participants who create handwritten notes work in a quiet classroom for 30 minutes. Participants who type their notes work in a busy computer room for 45 minutes.
The IV should be the method of producing notes:
Handwriting
Typing
However, the conditions also differ in:
Noise level.
Testing location.
Time allowed.
Each of these factors could affect test performance, so they are extraneous variables.
The researcher should make these aspects of the conditions consistent.
Controlling extraneous variables
Control of variables means reducing or managing the influence of factors other than the independent variable.
The aim is to make the conditions as similar as possible, apart from the intended change in the IV.
Possible controls include:
Giving every participant the same instructions.
Allowing the same amount of time in each condition.
Using the same equipment.
Testing participants in the same environment.
Presenting materials in the same way.
Keeping the researcher’s behaviour consistent.
Using tasks of equal difficulty.
Controlling the order in which activities occur.
Randomly allocating participants to conditions where appropriate.
The AQA specification also includes random allocation, counterbalancing, randomisation, standardisation and control groups. These are considered in detail in procedures used to improve experimental control.
Standardisation and control
Standardisation involves using the same procedure for all participants, except for the deliberate manipulation of the IV.
A standardised procedure might specify:
The exact instructions read to participants.
The materials provided.
The length of the task.
The equipment used.
The order in which activities occur.
How the DV is measured.
How the researcher responds to participant questions.
Standardisation helps prevent unintended differences between conditions.
Example
A researcher investigates whether encouragement affects persistence on a puzzle.
If one investigator says, “You’re doing brilliantly, keep going,” while another simply says, “Continue,” the amount of encouragement is not standardised.
If encouragement is the IV, the researcher should use an agreed script for each condition. If encouragement is not the IV, the researcher should give the same neutral response to every participant.
Controlling variables across conditions
Consider an experiment comparing learning in silence with learning while music is played.
Feature | Suitable control |
Word list | Use the same list or equivalent lists |
Learning time | Give every participant the same amount of time |
Instructions | Read the same standardised instructions |
Room | Use the same room or rooms with equivalent conditions |
Music equipment | Use the same device and volume |
Recall period | Give every participant the same recall time |
Researcher behaviour | Use the same neutral interaction |
Scoring | Apply the same scoring rules to every response |
The presence or absence of music should be the only planned difference between the conditions.
Control does not mean removing all variation
Researchers cannot always remove every possible extraneous variable. Human behaviour is influenced by many factors, and participants will never be completely identical.
The aim is to identify variables that are most likely to affect the DV and control them where practical.
An effective exam response should therefore explain:
Which extraneous variable may affect the results.
How it may influence the DV.
What the researcher could do to control it.
For example:
Participants in the afternoon condition may be more tired than those tested in the morning, which could reduce their attention scores. The researcher should test both conditions at similar times of day.
Variables and experimental design
The experimental design affects which extraneous variables are most important.
Repeated measures design
The same participants complete every condition.
This reduces the influence of differences between participants because each person is compared with themselves. However, order effects may become an extraneous influence.
The researcher may need to counterbalance the order of conditions.
Independent groups design
Different participants complete each condition.
There are no order effects across conditions, but differences between the groups may affect the DV. Random allocation may reduce systematic differences between the groups.
Matched pairs design
Different participants are matched on a characteristic relevant to the investigation.
Matching may reduce important differences between groups, but participants cannot be matched on every possible characteristic.
These relationships are explained further in organising participants across experimental conditions.
Demand characteristics as an extraneous influence
Demand characteristics occur when participants notice features of a study that reveal its purpose. They may then alter their behaviour because they think they know what the researcher expects.
For example, participants may realise that the researcher expects music to reduce concentration. Some may try harder in the music condition to challenge this expectation.
Demand characteristics may therefore affect the DV independently of the IV.
Researchers may reduce this problem by:
Avoiding unnecessary clues about the aim.
Using neutral instructions.
Making the conditions less obvious where appropriate.
Standardising the information given to participants.
Investigator effects as an extraneous influence
Investigator effects occur when a researcher’s behaviour or expectations influence participants or the recording of results.
For example, a researcher may:
Give more encouragement in one condition.
Explain instructions more clearly to some participants.
Use a different tone of voice.
Record ambiguous responses in a way that supports the expected outcome.
Standardised instructions, clearer scoring systems and investigator training may reduce these effects.
Both concepts are developed in recognising participant and researcher influences.
What is operationalisation?
Operationalisation means defining a variable precisely so that it can be manipulated or measured.
Psychologists often study ideas such as memory, stress, aggression, attraction and concentration. These cannot be measured directly until the researcher decides exactly what observable or measurable outcome will represent them.
Operationalisation turns a general concept into a practical research variable.
For example:
General concept | Possible operationalisation |
Memory | Number of words correctly recalled from a list of 20 |
Concentration | Number of targets correctly identified in three minutes |
Helping behaviour | Number of objects voluntarily picked up for another person |
Aggressive behaviour | Frequency of hitting, kicking or pushing during a ten-minute observation |
Task persistence | Number of seconds spent attempting an unsolved puzzle |
Academic performance | Score out of 30 on a specified test |
These are possible operational definitions. Their suitability depends on the aim and procedure of the investigation.
Operationalising the independent variable
To operationalise an IV, the researcher must state exactly how the conditions differ.
A vague IV would be:
Type of environment.
A clearer operationalisation would be:
Completing the task in silence compared with completing the task while a recording of café noise is played.
Another vague IV would be:
Amount of revision.
A clearer operationalisation would be:
Revising the material for ten minutes compared with revising it for 30 minutes.
The conditions should be specific enough for another researcher to reproduce them.
Operationalising the dependent variable
To operationalise a DV, the researcher must state exactly how the outcome will be measured.
A vague DV would be:
Memory.
A clearer DV would be:
The number of words correctly recalled from a list of 15 words within 90 seconds.
A vague DV would be:
Concentration.
A clearer DV would be:
The number of correct responses on a 25-item visual-search task completed within five minutes.
The operational definition should include relevant details such as:
What is being counted or scored.
The task being used.
The maximum possible score, where relevant.
The period during which the behaviour is measured.
The units in which the result will be recorded.
Features of a clear operational definition
A good operational definition should be:
Precise
It should explain exactly what is manipulated or measured.
Observable or measurable
Another researcher should be able to determine the value of the variable.
Replicable
The description should be detailed enough for another researcher to repeat the procedure.
Relevant
The measure should relate logically to the psychological concept in the research aim.
Practical
The variable should be measurable using the available procedure and resources.
Operationalising behaviour in observations
In observational research, operationalisation usually involves constructing behavioural categories.
For example, “social interaction” is too vague to record directly.
It might be operationalised as:
Begins a conversation with another person.
Responds verbally when another person speaks.
Offers an object to another person.
Joins another person’s activity.
The observer can record the frequency of these visible or audible behaviours.
This builds on constructing clear behavioural categories.
Operationalising variables in self-report research
In questionnaires and interviews, variables may be operationalised through participants’ responses.
For example, “hours of sleep” could be measured by asking:
How many hours and minutes did you sleep last night?
“Confidence about an examination” might be measured through a closed question that asks participants to select a number on a defined rating scale.
The wording must make clear:
The time period being considered.
The meaning of each response option.
How the response will be scored.
Vague terms such as “often”, “regularly” or “a lot” may be interpreted differently unless they are defined.
Operationalising variables in an experiment
Consider this research aim:
To investigate whether sleep affects concentration.
Both variables require operationalisation.
One possible version is:
IV: participants who report having slept fewer than six hours compared with participants who report having slept eight hours or more during the previous night.
DV: the number of correct responses on a 30-item attention task completed in five minutes.
The exact operationalisation should be described when explaining the procedure.
Why operationalisation matters
Clear operationalisation may improve an investigation because it:
Allows variables to be measured consistently.
Reduces differences in interpretation.
Makes the procedure easier to replicate.
Helps researchers compare participants or conditions.
Makes scoring decisions clearer.
Allows the aim and hypothesis to be tested using evidence.
Poor operationalisation can create ambiguity.
For example, if “good memory” is defined only as remembering “many words”, researchers may disagree about how many words count as “many”.
Operationalisation and validity
A variable can be precisely measured without necessarily being a good measure of the intended concept.
For example, a researcher might operationalise concentration as the number of times a participant looks at a worksheet. This is easy to record, but looking at a worksheet does not always mean that the person is concentrating.
Researchers must therefore consider whether the operational definition genuinely represents what they intend to investigate.
The specification requires students to understand validity and ways of improving it, which is explored further in face, concurrent, ecological and temporal validity.
Operationalisation and reliability
Clear operationalisation may improve reliability because researchers can apply the same measurement rules consistently.
For example, “aggressive behaviour” is subjective, while “hits, kicks or pushes another person” is more precise.
Different observers are more likely to agree when the behaviour is clearly defined.
However, a precise measure is not automatically reliable. Researchers must still apply the procedure and scoring rules consistently.
Piloting operational definitions
A researcher can test operational definitions during a pilot study.
A pilot might reveal that:
The conditions of the IV are not sufficiently different.
Participants do not understand the task.
The DV produces almost identical scores for everyone.
A measure is too difficult or too easy.
Observers interpret a behavioural category differently.
Scoring rules are incomplete.
An extraneous variable has not been controlled.
The researcher can then revise the manipulation, measurement or control procedures before the full investigation.
This links to testing and improving a proposed procedure.
Variables in correlations
A correlation investigates the relationship between two co-variables.
Researchers do not normally describe the variables in a correlation as an IV and a DV because neither co-variable is manipulated to investigate its effect on the other.
For example, a researcher may measure:
Hours spent revising.
Score on a psychology test.
These are co-variables. The researcher examines whether they are related but does not manipulate revision time or establish that one variable caused the other.
This distinction is important when studying relationships between co-variables.
A complete variables example
A psychologist investigates whether completing a mindfulness activity before a test affects concentration.
Participants are allocated to one of two conditions:
Condition A completes a ten-minute mindfulness activity.
Condition B sits quietly for ten minutes.
All participants then complete the same concentration task.
Independent variable
Whether participants complete:
A ten-minute mindfulness activity.
Ten minutes of quiet sitting.
Dependent variable
The number of correct responses on the concentration task.
A fuller operationalisation would state the number of items, the time allowed and the scoring rules.
Possible extraneous variables
Different instructions between conditions.
Different rooms.
Different levels of background noise.
Different time limits.
Differences in the way the researcher interacts with participants.
Participants having previous experience of the concentration task.
Possible controls
Use standardised instructions.
Test participants in the same environment.
Use the same time limit and equipment.
Apply identical scoring rules.
Ensure the researcher responds consistently.
Randomly allocate participants to conditions.
Variables and operationalisation A-Level Psychology revision: answering application questions
Questions about variables are often based on unfamiliar scenarios.
A strong answer should use details from the scenario rather than giving a generic definition.
Identifying an IV
State both conditions where possible.
Weak answer:
The IV is noise.
Stronger answer:
The IV is whether participants complete the task in silence or while background noise is played.
Identifying a DV
State exactly what is measured.
Weak answer:
The DV is performance.
Stronger answer:
The DV is the number of correct responses on the 20-item concentration task.
Identifying an extraneous variable
Explain how it could affect the DV.
Weak answer:
Time of day is an extraneous variable.
Stronger answer:
Time of day is an extraneous variable because participants tested later may be more tired, which could reduce their concentration scores.
Suggesting a control
Give a practical response linked to the variable.
Weak answer:
Control the time.
Stronger answer:
Test both conditions at the same time of day so that differences in tiredness are less likely to affect the concentration scores.
Designing variables for an investigation
When planning an investigation:
State a clear aim.
Identify the IV and its conditions.
Operationalise each IV condition precisely.
Identify the DV.
State exactly how the DV will be measured.
Identify likely extraneous variables.
Select practical ways of controlling them.
Pilot the manipulation and measurement.
Revise the procedure where necessary.
These decisions form an important part of developing a complete research proposal.
Key Words 🔑
Key word | Student-friendly definition | How it may be used in an exam |
Variable | A feature of an investigation that can change or take different values. | Identify or describe features being changed, measured or controlled. |
Independent variable | The variable changed or selected so that its effect can be investigated. | Identify what differs between experimental conditions. |
Dependent variable | The outcome measured to determine whether it changes with the IV. | State exactly what data the researcher records. |
Extraneous variable | Any variable other than the IV that could affect the DV. | Identify an alternative influence on the results. |
Manipulation | Deliberately changing the IV to create different experimental conditions. | Explain how the researcher produces the conditions. |
Control | Reducing or managing the influence of variables other than the IV. | Suggest how a researcher could improve an investigation. |
Condition | One version of the experimental situation created through the IV. | Describe the different versions of the study. |
Operationalisation | Defining a variable precisely so it can be manipulated or measured. | Turn a general concept into a clear research variable. |
Standardisation | Keeping instructions, materials and procedures consistent. | Suggest a way of controlling unwanted differences. |
Demand characteristics | Features of a study that may reveal its purpose and change participant behaviour. | Identify an unintended influence on the DV. |
Investigator effects | Ways in which a researcher may influence participants or the recording of results. | Suggest standardisation or clearer scoring procedures. |
Co-variable | One of the two measured variables in a correlation. | Distinguish a correlation from an experiment. |
Common Mistakes ⚠️
Mistake: Saying that the independent variable is the variable that is measured.
Why this is incorrect:The IV is changed or selected. The DV is measured.
How to improve:Ask what differs between the conditions and what outcome is recorded.
Mistake: Naming the IV without giving its conditions.
Why this is incorrect:An answer such as “music” does not fully identify how the variable differs.
How to improve:State both conditions, such as learning in silence compared with learning while music is played.
Mistake: Describing the DV using a vague concept.
Why this is incorrect:Terms such as “memory”, “performance” or “concentration” do not state what the researcher records.
How to improve:Give a measurable outcome, such as the number of correct answers on a specified task.
Mistake: Identifying every feature of a study as an extraneous variable.
Why this is incorrect:An extraneous variable must have the potential to influence the DV.
How to improve:Explain how the factor could affect the measured outcome.
Mistake: Identifying an extraneous variable without suggesting a relevant control.
Why this is incorrect:A control must directly address the problem identified.
How to improve:Link the variable and control clearly. If testing time could affect tiredness, test the conditions at equivalent times.
Mistake: Saying that all extraneous variables can be eliminated.
Why this is incorrect:Researchers cannot remove every source of variation in human behaviour.
How to improve:Explain that researchers aim to reduce or manage the most important extraneous influences.
Mistake: Treating operationalisation as simply naming the variable.
Why this is incorrect:Operationalisation requires a precise explanation of how the variable is changed or measured.
How to improve:Include the conditions, task, score, time period or observable behaviour used.
Mistake: Using IV and DV for a correlation.
Why this is incorrect:Correlations measure relationships between co-variables rather than manipulating an IV and measuring its effect on a DV.
How to improve:Use the term co-variable when neither variable is experimentally manipulated.
Exam-Style Questions ✍️
Question 1
Define an independent variable. (1 mark)
Question 2
Define an extraneous variable. (1 mark)
Question 3
A psychologist investigates whether participants remember more words when they learn them in silence or while listening to music.
Identify the independent variable and the dependent variable. (2 marks)
Question 4
Explain what is meant by operationalisation. (2 marks)
Question 5
A researcher wants to investigate whether tiredness affects concentration.
Operationalise:
The independent variable.
The dependent variable.
(4 marks)
Question 6
A psychologist investigates whether working alone or in a group affects the time taken to complete a puzzle.
Participants working alone complete the task in a quiet room. Participants working in a group complete it in a room next to a busy corridor.
Identify one extraneous variable and explain how the psychologist could control it. (3 marks)
Question 7
A researcher investigates whether written or spoken instructions affect task accuracy. The written-instructions group is given ten minutes to complete the task, while the spoken-instructions group is given fifteen minutes.
Explain why time allowed is an extraneous variable in this investigation. Suggest an appropriate control. (4 marks)
Question 8
A psychologist wants to investigate whether background noise affects concentration. The psychologist writes:
IV: noise
DV: concentration
Explain why these variables have not been operationalised clearly. Provide an improved operationalisation of each variable. (6 marks)
Question 9
A researcher investigates whether the presence of a mobile phone affects performance on a reasoning task.
Participants complete the task either with a phone placed on the desk or with no phone present. Different researchers conduct the two conditions, and one researcher gives participants more encouragement than the other.
Identify the independent variable, dependent variable and one extraneous variable. Explain how the extraneous variable could be controlled. (6 marks)
Question 10
A psychologist plans to investigate whether studying with background music affects memory.
Design the variables for this experiment. In your answer:
Operationalise the independent variable.
Operationalise the dependent variable.
Identify two possible extraneous variables.
Explain how each extraneous variable could be controlled.
(8 marks)
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