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the researcher measuring as the outcome?","correct":false,"explanation":"The measured outcome is the dependent variable, not the independent variable. The IV is identified by asking what the researcher changes between conditions."},{"text":"What is the researcher keeping constant throughout?","correct":false,"explanation":"Factors kept constant are control variables rather than the independent variable. The IV is the factor deliberately changed between the experimental conditions."},{"text":"What is the researcher using to allocate participants?","correct":false,"explanation":"Participant allocation identifies the experimental design, such as independent groups or repeated measures. The IV is the factor the researcher changes between conditions."}]},{"id":"63afd89b-9f64-44e7-8dfb-b9adb425e350","cardType":"basic","points":1,"front":"In an experiment, what should you ask to identify the DV?","back":"What outcome is being recorded?","mcqOptions":[{"text":"What outcome is being recorded?","correct":true,"explanation":"The dependent variable is the measured result of the experiment, so it is identified by finding the outcome that the researcher records."},{"text":"What variable is being changed?","correct":false,"explanation":"The variable deliberately changed is the independent variable, not the dependent variable. The DV is the outcome recorded to assess the change’s effect."},{"text":"What factor is being kept constant?","correct":false,"explanation":"A factor kept constant is a control variable, used to prevent confounding. The DV is the outcome measured and recorded by the researcher."},{"text":"What method assigns participants to conditions?","correct":false,"explanation":"The method of assigning participants concerns experimental design rather than the dependent variable. The DV is the recorded outcome that may respond to the IV."}]},{"id":"97f55a08-e93d-448c-926f-7202d310da99","cardType":"cloze","points":null,"front":"An experiment changes one variable, measures another, and keeps everything else the same to test [ ].","back":"An experiment changes one variable, measures another, and keeps everything else the same to test cause and effect.","mcqOptions":[{"text":"cause and effect","correct":true,"explanation":"Manipulating one variable while measuring another and controlling other factors allows an experiment to establish whether changes in the IV cause changes in the DV."},{"text":"correlation and association","correct":false,"explanation":"Correlation describes variables occurring together without showing that one causes the other. A controlled experiment is designed to test cause and effect."},{"text":"reliability and validity","correct":false,"explanation":"Reliability and validity concern the quality and consistency of research methods and measurements. Manipulating an IV and measuring a DV tests cause and effect."},{"text":"nature and nurture","correct":false,"explanation":"Nature and nurture describe biological and environmental influences on behaviour, not the purpose of experimental control. Experiments manipulate variables to test cause and effect."}]},{"id":"6f43e57b-bbfe-4ea4-9d8e-27886ddafc8c","cardType":"basic","points":1,"front":"In Loftus & Palmer, what was the IV?","back":"The wording of the critical question.","mcqOptions":[{"text":"The wording of the critical question.","correct":true,"explanation":"Loftus and Palmer manipulated the verb used in the critical question, such as “smashed” or “hit”, making the question’s wording the independent variable."},{"text":"The estimated speed reported by participants.","correct":false,"explanation":"Reported speed was measured rather than manipulated, so it was the dependent variable. The independent variable was the wording of the critical question."},{"text":"The actual speed of the cars.","correct":false,"explanation":"Participants watched the same collision footage, so the cars’ actual speed was not manipulated. The critical question’s wording was the independent variable."},{"text":"The number of cars shown in the film.","correct":false,"explanation":"The number of cars was not varied between the relevant conditions. Loftus and Palmer manipulated the wording of the critical question given after the film."}]},{"id":"ff339bd7-24b6-47cf-92c2-14905592ad4b","cardType":"basic","points":1,"front":"In Loftus & Palmer, what was the DV?","back":"Participants’ estimated speed of the cars.","mcqOptions":[{"text":"Participants’ estimated speed of the cars.","correct":true,"explanation":"The dependent variable was participants’ numerical estimate of the cars’ speed, recorded after they received a critical question containing a particular verb."},{"text":"Participants’ version of the critical question after the film.","correct":false,"explanation":"The version of the critical question was assigned by the researchers and therefore formed the independent variable. The dependent variable was participants’ estimated speed."},{"text":"Participants’ actual speed while watching the film.","correct":false,"explanation":"Participants were watching collision footage rather than driving, so they had no actual driving speed to measure. Their estimate of the cars’ speed was recorded."},{"text":"Participants’ viewing time for the collision film.","correct":false,"explanation":"Viewing time was not the recorded outcome in this experiment. The dependent variable was the speed participants estimated after watching the collision footage."}]},{"id":"bdc39157-ad12-4c21-862c-7c338ad5cf63","cardType":"basic","points":1,"front":"In Asch’s conformity research, what IV involved the number of confederates?","back":"The size of the majority group.","mcqOptions":[{"text":"The size of the majority group.","correct":true,"explanation":"Asch varied how many confederates formed the incorrect majority, so the size of the majority group was the independent variable in this manipulation."},{"text":"The unanimity of the majority group.","correct":false,"explanation":"Unanimity was investigated in a different variation involving a dissenter. When the manipulated factor was the number of confederates, the IV was majority-group size."},{"text":"The difficulty of the line judgement.","correct":false,"explanation":"The number-of-confederates manipulation concerned group size, not task difficulty. The independent variable was the size of the majority giving the incorrect answer."},{"text":"The rate of participant conformity.","correct":false,"explanation":"The conformity rate was the measured outcome and therefore the dependent variable. The independent variable was the number of confederates in the majority group."}]},{"id":"0171d1ea-87cc-46b1-840e-09c4658d272c","cardType":"basic","points":1,"front":"In Asch, how was conformity often measured as the DV?","back":"Whether the participant gave the same incorrect answer as the majority.","mcqOptions":[{"text":"Whether the participant gave the same incorrect answer as the majority.","correct":true,"explanation":"Conformity occurred when the participant adopted the majority’s clearly incorrect judgement, so matching the majority’s wrong answer provided a measurable dependent variable."},{"text":"Whether the participant gave the correct answer despite the majority.","correct":false,"explanation":"Giving the correct answer despite majority pressure indicates independence or non-conformity. Conformity was measured by matching the majority’s same incorrect answer."},{"text":"Whether the participant gave a different incorrect answer from the majority.","correct":false,"explanation":"An independently chosen wrong answer does not show conformity because it does not match the group. The DV recorded whether participants gave the majority’s same incorrect answer."},{"text":"Whether the confederates gave the same incorrect answer as one another.","correct":false,"explanation":"The confederates’ agreed answers created the experimental pressure and were predetermined. Conformity was measured from whether the genuine participant copied their incorrect answer."}]},{"id":"e939809d-6d11-4aa5-9822-758daeb83891","cardType":"cloze","points":null,"front":"A strong DV should be measurable, objective and [ ].","back":"A strong DV should be measurable, objective and relevant.","mcqOptions":[{"text":"relevant","correct":true,"explanation":"A useful dependent variable must directly measure the behaviour or outcome named in the hypothesis, making relevance essential alongside measurability and objectivity."},{"text":"manipulated","correct":false,"explanation":"The independent variable is manipulated, whereas the dependent variable is measured. A strong DV should instead be relevant to the hypothesis or behaviour under investigation."},{"text":"subjective","correct":false,"explanation":"Subjective measurements depend on personal judgement and can reduce consistency, directly conflicting with objectivity. A strong dependent variable should be relevant to the research aim."},{"text":"unrelated","correct":false,"explanation":"An outcome unrelated to the hypothesis would not provide meaningful evidence about the IV’s effect. A strong dependent variable must be relevant to the investigation."}]},{"id":"f5694d17-c66b-4155-a3e9-81ce3f79fb90","cardType":"basic","points":2,"front":"Why are extraneous variables a problem in experiments?","back":"They make it harder to know whether the IV caused the DV change.","mcqOptions":[{"text":"They make it harder to know whether the IV caused the DV change.","correct":true,"explanation":"Extraneous variables provide alternative explanations for changes in the DV, reducing confidence that manipulation of the IV produced the observed effect."},{"text":"They make it harder to know whether the DV caused the IV change.","correct":false,"explanation":"This reverses the experimental relationship: the researcher manipulates the IV and measures the DV. Extraneous variables obscure whether the IV caused the change in the DV."},{"text":"They make it harder to know whether the sample represents the population.","correct":false,"explanation":"Population representativeness concerns sampling and generalisability, not extraneous variables. Extraneous variables are problematic because they obscure whether the IV caused the change in the DV."},{"text":"They make it harder to know whether the DV was measured consistently.","correct":false,"explanation":"Consistent measurement concerns reliability rather than control of extraneous variables. Extraneous variables create alternative explanations, making it harder to establish that the IV caused the DV change."}]},{"id":"99986a72-434f-4c62-9a89-5f2cd2116e8a","cardType":"basic","points":2,"front":"In the music and memory example, why is time of day an extraneous variable?","back":"It could affect alertness and memory score.","mcqOptions":[{"text":"It could affect alertness and memory score.","correct":true,"explanation":"Alertness often varies with time of day and can influence memory performance. This could change participants’ scores independently of the music condition being investigated."},{"text":"It could affect music volume and sound quality.","correct":false,"explanation":"Volume and sound quality depend on the equipment and experimental settings, not directly on the time of day. Time matters because it can affect alertness and memory score."},{"text":"It could affect sample size and participant allocation.","correct":false,"explanation":"Sample size and allocation are determined by the researcher’s design and procedure. Time of day is extraneous because it may alter alertness and therefore memory scores."},{"text":"It could affect music type and experimental hypothesis.","correct":false,"explanation":"The chosen music and hypothesis should be established before data collection and do not change with the clock. Time of day may instead affect alertness and memory performance."}]},{"id":"867261ff-c50f-4888-a5a8-e861f0be05e4","cardType":"cloze","points":null,"front":"A confounding variable is an extraneous variable that varies [ ].","back":"A confounding variable is an extraneous variable that varies systematically with the IV.","mcqOptions":[{"text":"systematically with the IV","correct":true,"explanation":"A confounding variable changes consistently alongside the IV, so its influence cannot be separated from the IV’s effect on the DV."},{"text":"randomly between participants","correct":false,"explanation":"Random variation may be an extraneous influence, but it is not necessarily confounding. A variable becomes confounding when it varies systematically with the IV."},{"text":"independently of the DV","correct":false,"explanation":"Independence from the DV does not define a confounding variable. Confounding occurs when an extraneous variable changes systematically with the IV and offers an alternative explanation."},{"text":"equally across all conditions","correct":false,"explanation":"A variable held equal across conditions is controlled and cannot explain differences between them. A confounding variable instead varies systematically with the IV."}]},{"id":"38f4a250-780d-4beb-aa05-baf7a523d006","cardType":"basic","points":1,"front":"When does an extraneous variable become a confounding variable?","back":"When it changes systematically with the IV.","mcqOptions":[{"text":"When it changes systematically with the IV.","correct":true,"explanation":"Systematic co-variation means the extraneous variable differs consistently between IV conditions, making it impossible to tell which variable caused the observed DV change."},{"text":"When it changes randomly between participants.","correct":false,"explanation":"Random differences can increase unexplained variation, but they do not necessarily co-vary with the IV. Confounding occurs when the variable changes systematically with the IV."},{"text":"When it remains constant across all conditions.","correct":false,"explanation":"Keeping a variable constant controls it, preventing it from explaining condition differences. It becomes confounding only when it changes systematically with the IV."},{"text":"When it affects the DV but not the IV.","correct":false,"explanation":"An influence on the DV may make a variable extraneous, but it becomes confounding only if it also varies systematically with the IV conditions."}]},{"id":"0b96e15e-436f-42c2-b490-74846dda22fb","cardType":"basic","points":1,"front":"Which type of extraneous variable involves age, intelligence or motivation?","back":"Participant variables.","mcqOptions":[{"text":"Participant variables.","correct":true,"explanation":"Participant variables are individual differences between people, such as age, intelligence and motivation, which may affect the DV independently of the IV."},{"text":"Situational variables.","correct":false,"explanation":"Situational variables are features of the environment, such as noise, lighting and temperature. Age, intelligence and motivation are individual differences called participant variables."},{"text":"Experimenter effects.","correct":false,"explanation":"Experimenter effects occur when a researcher’s behaviour unintentionally influences participants or results. Age, intelligence and motivation are characteristics classified as participant variables."},{"text":"Order effects.","correct":false,"explanation":"Order effects arise from completing multiple conditions, commonly through practice or fatigue. Age, intelligence and motivation are pre-existing individual differences called participant variables."}]},{"id":"8885adfb-785f-4e75-8477-56c9dbed9f2f","cardType":"basic","points":1,"front":"Which type of extraneous variable involves noise, lighting or temperature?","back":"Situational variables.","mcqOptions":[{"text":"Situational variables.","correct":true,"explanation":"Situational variables are aspects of the experimental environment, including noise, lighting and temperature, that could influence participants’ behaviour or performance."},{"text":"Participant variables.","correct":false,"explanation":"Participant variables are individual differences such as age, intelligence and motivation. Noise, lighting and temperature belong to the experimental environment and are situational variables."},{"text":"Experimenter effects.","correct":false,"explanation":"Experimenter effects result from the researcher unintentionally influencing participants. Noise, lighting and temperature are environmental features, so they are classified as situational variables."},{"text":"Order effects.","correct":false,"explanation":"Order effects involve practice, fatigue or boredom caused by experiencing several conditions. Noise, lighting and temperature are environmental influences known as situational variables."}]},{"id":"dfa12e47-e3f5-4335-9e6e-cbe944ab235e","cardType":"basic","points":1,"front":"Which extraneous variable involves the researcher unintentionally influencing participants?","back":"Experimenter effects.","mcqOptions":[{"text":"Experimenter effects.","correct":true,"explanation":"Experimenter effects occur when a researcher unintentionally influences participants through expectations, tone, behaviour or other cues, potentially affecting the measured outcome."},{"text":"Participant variables.","correct":false,"explanation":"Participant variables are individual differences such as intelligence, age or motivation. Unintentional influence from the researcher is instead classified as an experimenter effect."},{"text":"Situational variables.","correct":false,"explanation":"Situational variables are environmental features such as noise, temperature or lighting. Influence arising from the researcher’s behaviour is classified as an experimenter effect."},{"text":"Order effects.","correct":false,"explanation":"Order effects result from the sequence of repeated conditions, including practice and fatigue. Unintentional influence caused by the researcher is known as an experimenter effect."}]},{"id":"1af47191-4783-4ecd-a71a-2f43722f308b","cardType":"basic","points":1,"front":"Which extraneous variable involves practice or fatigue across conditions?","back":"Order effects.","mcqOptions":[{"text":"Order effects.","correct":true,"explanation":"Order effects occur in repeated measures designs when experience of earlier conditions causes practice, fatigue or boredom that influences performance in later conditions."},{"text":"Participant variables.","correct":false,"explanation":"Participant variables are pre-existing individual differences, such as age or motivation. Practice and fatigue caused by completing several conditions are specifically order effects."},{"text":"Situational variables.","correct":false,"explanation":"Situational variables are features of the testing environment, such as lighting and noise. Practice or fatigue resulting from condition sequence are classified as order effects."},{"text":"Experimenter effects.","correct":false,"explanation":"Experimenter effects arise when the researcher unintentionally influences participants. Practice and fatigue developing as participants complete conditions are instead examples of order effects."}]},{"id":"104e0a0d-e421-4808-a4b0-4f2c3c4b6195","cardType":"cloze","points":null,"front":"Standardisation means using the same [ ] for all participants.","back":"Standardisation means using the same procedure for all participants.","mcqOptions":[{"text":"procedure","correct":true,"explanation":"Standardisation requires every participant to experience the same procedure. This keeps the study consistent and prevents procedural differences from becoming extraneous variables."},{"text":"result","correct":false,"explanation":"Participants are not expected to produce the same result, because genuine individual differences may remain. Standardisation means using the same procedure for everyone."},{"text":"hypothesis","correct":false,"explanation":"A hypothesis is the researcher’s testable prediction, not what is kept consistent across participants. Standardisation requires the same procedure to be used for everyone."},{"text":"sample","correct":false,"explanation":"A sample is the group selected to participate and cannot be reused for every participant. Standardisation means applying the same procedure to all participants."}]},{"id":"d9c9eefc-c851-46c4-b41f-33b0644d8421","cardType":"basic","points":2,"front":"How does standardisation improve replicability?","back":"Another researcher can repeat the study in the same way.","mcqOptions":[{"text":"Another researcher can repeat the study in the same way.","correct":true,"explanation":"A standardised procedure gives other researchers clear, consistent steps to follow, allowing them to repeat the study in the same way and test its reliability."},{"text":"Another researcher can obtain the same results.","correct":false,"explanation":"Replication does not guarantee identical results, because samples and circumstances can differ. Standardisation improves replicability by allowing another researcher to repeat the study in the same way."},{"text":"Another researcher can apply the findings to the same population.","correct":false,"explanation":"Applying findings to a population concerns generalisability rather than replicability. Standardisation improves replicability because another researcher can repeat the study in the same way."},{"text":"Another researcher can remove all participant bias.","correct":false,"explanation":"Standardisation cannot remove all participant bias, such as demand characteristics. It improves replicability by enabling another researcher to repeat the study in the same way."}]},{"id":"7f477559-2f98-4a7f-9cfa-cbc6bf940118","cardType":"basic","points":2,"front":"How does random allocation help control participant variables?","back":"It spreads participant differences evenly across conditions.","mcqOptions":[{"text":"It spreads participant differences evenly across conditions.","correct":true,"explanation":"Random allocation gives every participant an equal chance of entering each condition, so individual differences should be distributed evenly rather than systematically affecting one condition."},{"text":"It removes participant differences entirely from the study.","correct":false,"explanation":"Random allocation cannot eliminate individual differences between participants. It controls their influence by spreading participant differences evenly across the experimental conditions."},{"text":"It places similar participants together in one condition.","correct":false,"explanation":"Grouping similar participants in one condition would create systematic differences and confound the results. Random allocation aims to spread participant differences evenly across conditions."},{"text":"It ensures every participant completes all experimental conditions.","correct":false,"explanation":"Having everyone complete every condition describes a repeated measures design, not random allocation. Random allocation controls participant variables by spreading differences evenly across conditions."}]},{"id":"1a013db0-2834-416d-bfda-86350dfd0b8a","cardType":"basic","points":1,"front":"Which control method is best for order effects in repeated measures designs?","back":"Counterbalancing.","mcqOptions":[{"text":"Counterbalancing.","correct":true,"explanation":"Counterbalancing varies the order in which conditions are completed, distributing practice, fatigue and boredom effects so they do not consistently favour one condition."},{"text":"Random allocation.","correct":false,"explanation":"Random allocation distributes participants between conditions in an independent groups design; it does not address order effects. Repeated measures order effects are controlled using counterbalancing."},{"text":"Matching.","correct":false,"explanation":"Matching creates similar groups to reduce participant differences, rather than controlling practice or fatigue caused by condition order. Counterbalancing is the appropriate method."},{"text":"Placebo control.","correct":false,"explanation":"A placebo controls expectations about receiving a treatment, not practice, fatigue or boredom across successive conditions. Counterbalancing is used to control order effects."}]},{"id":"ec752ecc-82c3-423d-b03f-0b4c77e1498a","cardType":"basic","points":2,"front":"How does counterbalancing control order effects?","back":"Different participants complete conditions in different orders.","mcqOptions":[{"text":"Different participants complete conditions in different orders.","correct":true,"explanation":"Using different condition orders distributes practice, fatigue and boredom effects across conditions, preventing one condition from being consistently advantaged or disadvantaged by its position."},{"text":"Different participants complete conditions in the same order.","correct":false,"explanation":"Using the same order for everyone allows practice or fatigue to affect one condition systematically. Counterbalancing instead uses different orders for different participants."},{"text":"Each participant completes only one experimental condition.","correct":false,"explanation":"Completing only one condition describes an independent groups design, not counterbalancing. Counterbalancing retains repeated measures but gives different participants different condition orders."},{"text":"All participants complete conditions with different instructions.","correct":false,"explanation":"Changing instructions would reduce standardisation and could introduce a confounding variable. Counterbalancing controls order effects by varying the order of conditions across participants."}]},{"id":"52fc8239-733d-4188-94c7-d6a5d977822b","cardType":"basic","points":1,"front":"What is the purpose of a control group?","back":"To compare the treatment condition against a baseline.","mcqOptions":[{"text":"To compare the treatment condition against a baseline.","correct":true,"explanation":"A control group provides a baseline showing what happens without the experimental treatment, allowing researchers to judge whether changes are attributable to that treatment."},{"text":"To compare the treatment condition against a population average.","correct":false,"explanation":"A population average is not an experimental baseline and may differ from the sample in uncontrolled ways. A control group provides a baseline for comparison with treatment."},{"text":"To compare the treatment condition against a researcher’s prediction.","correct":false,"explanation":"A researcher’s prediction is the hypothesis, not a comparison group producing empirical data. The control group provides a baseline against which treatment effects can be assessed."},{"text":"To compare the treatment condition against a participant variable.","correct":false,"explanation":"Participant variables are individual characteristics that may influence results, not suitable comparison conditions. A control group supplies the baseline needed to evaluate the treatment."}]},{"id":"4adc6d8c-5650-4b95-b319-065206d3c5e6","cardType":"cloze","points":null,"front":"Operationalisation means defining a variable precisely so it can be [ ] in an observable way.","back":"Operationalisation means defining a variable precisely so it can be measured or manipulated in an observable way.","mcqOptions":[{"text":"measured or manipulated","correct":true,"explanation":"Operationalisation converts an abstract variable into a precise, observable form. A dependent variable must be measurable, while an independent variable must be manipulable through defined conditions."},{"text":"described or discussed","correct":false,"explanation":"Merely describing or discussing a variable does not specify how it will be observed in practice. Operationalisation defines it precisely so it can be measured or manipulated."},{"text":"predicted or inferred","correct":false,"explanation":"Prediction belongs to hypothesis formation, while inference belongs to interpreting results. Operationalisation specifies observable procedures through which a variable can be measured or manipulated."},{"text":"controlled or eliminated","correct":false,"explanation":"Controlling or eliminating variables concerns managing extraneous influences, not defining the variable under investigation. Operationalisation makes a variable measurable or manipulable in an observable way."}]},{"id":"f68f7030-d766-4cd0-88ad-88eca4c084b5","cardType":"basic","points":1,"front":"For an IV, what must operationalisation state?","back":"The exact conditions.","mcqOptions":[{"text":"The exact conditions.","correct":true,"explanation":"Operationalising an independent variable requires stating its precise conditions or levels, so it is clear exactly how the researcher will manipulate it."},{"text":"The exact participant responses.","correct":false,"explanation":"Participant responses are normally measurements of the dependent variable, not the independent variable. Operationalising the IV requires specifying the exact conditions used in the manipulation."},{"text":"The exact sampling methods.","correct":false,"explanation":"Sampling methods explain how participants are selected, rather than how the independent variable is manipulated. IV operationalisation must state the exact experimental conditions."},{"text":"The exact statistical tests.","correct":false,"explanation":"Statistical tests are selected to analyse results after data collection and do not define the independent variable. IV operationalisation specifies the exact conditions being compared."}]},{"id":"69422b2c-cd4d-43c3-9a0b-beb0d0c07c64","cardType":"basic","points":1,"front":"For a DV, what must operationalisation state?","back":"Exactly how the outcome is measured.","mcqOptions":[{"text":"Exactly how the outcome is measured.","correct":true,"explanation":"Operationalising the DV requires a precise description of how the observed outcome will be measured, allowing researchers to collect consistent data and replicate the procedure."},{"text":"Exactly how the condition is manipulated.","correct":false,"explanation":"This describes operationalisation of the independent variable, not the dependent variable. For a DV, researchers must state exactly how the outcome is measured."},{"text":"Exactly how the participants are allocated.","correct":false,"explanation":"Allocating participants to conditions is part of the experimental design rather than operationalising the DV. Operationalisation must specify exactly how the outcome is measured."},{"text":"Exactly how the extraneous variables are controlled.","correct":false,"explanation":"Managing possible confounding variables concerns experimental control, not measurement of the DV. The operational definition must state exactly how the outcome is measured."}]},{"id":"df037131-fdd0-41d6-8249-d80525ff5b27","cardType":"basic","points":1,"front":"How could “stress” be operationalised using self-report?","back":"Self-rated stress on a scale from 1 to 10.","mcqOptions":[{"text":"Self-rated stress on a scale from 1 to 10.","correct":true,"explanation":"A numerical self-rating converts the abstract concept of stress into measurable quantitative data. Specifying the 1 to 10 scale makes the operational definition clear and replicable."},{"text":"Researcher-rated stress on a scale from 1 to 10.","correct":false,"explanation":"A researcher’s judgement is an observational measure rather than a self-report measure. A suitable self-report operationalisation is self-rated stress on a scale from 1 to 10."},{"text":"Recorded heart rate on a scale from 1 to 10.","correct":false,"explanation":"Heart rate is a physiological measure, even if recorded numerically, and therefore is not self-report. Stress could instead be operationalised through a self-rating from 1 to 10."},{"text":"Number of errors on a scale from 1 to 10.","correct":false,"explanation":"The number of errors is a behavioural performance measure rather than participants’ own report of stress. Self-report requires participants to rate their stress, such as from 1 to 10."}]},{"id":"751af217-36ae-4568-b886-4c045c58b7d0","cardType":"basic","points":1,"front":"In an Asch-style study, how could group size be operationalised?","back":"One, three or six confederates giving the same wrong answer.","mcqOptions":[{"text":"One, three or six confederates giving the same wrong answer.","correct":true,"explanation":"Group size is made measurable by specifying the exact number of confederates present. Keeping their unanimous wrong answer constant ensures that only group size varies."},{"text":"One, three or six critical trials featuring the same wrong answer.","correct":false,"explanation":"Changing the number of critical trials operationalises exposure or trial frequency, not group size. Group size should be varied through one, three or six confederates."},{"text":"One, three or six answer choices including the same wrong answer.","correct":false,"explanation":"Varying answer choices changes the response format rather than the size of the majority. Group size is operationalised using one, three or six confederates giving the same wrong answer."},{"text":"One, three or six repetitions of the same wrong answer.","correct":false,"explanation":"Varying repetitions changes how often the majority answer is heard, not how many people form the group. The intended operationalisation uses one, three or six confederates."}]},{"id":"fe24a455-7ce6-4ab7-ac64-48f3dc1d238a","cardType":"basic","points":1,"front":"In an Asch-style study, how could conformity be operationalised?","back":"Percentage of critical trials with the same incorrect answer as the majority.","mcqOptions":[{"text":"Percentage of critical trials with the same incorrect answer as the majority.","correct":true,"explanation":"Conformity occurs when a participant adopts the majority’s incorrect response. Calculating its percentage across critical trials provides a precise quantitative measure of conformity."},{"text":"Percentage of critical trials with the correct answer despite the majority.","correct":false,"explanation":"Choosing the correct answer despite majority pressure measures resistance to conformity. Conformity is measured by the percentage of critical trials matching the majority’s incorrect answer."},{"text":"Percentage of critical trials with the fastest answer given after the majority.","correct":false,"explanation":"Response speed may indicate hesitation, but it does not show whether the participant conformed. Conformity requires measuring how often the participant gave the majority’s same incorrect answer."},{"text":"Percentage of critical trials with the lowest confidence rating after the majority.","correct":false,"explanation":"Confidence is a separate self-report variable and does not establish that participants adopted the group’s judgement. Conformity is shown by matching the majority’s incorrect answer."}]},{"id":"9c00ccb6-1a72-4cb4-bc1c-9eaa2f032d85","cardType":"cloze","points":null,"front":"Validity means whether a study or measure actually tests what it [ ].","back":"Validity means whether a study or measure actually tests what it claims to test.","mcqOptions":[{"text":"claims to test","correct":true,"explanation":"Validity concerns accuracy: a valid study or measure genuinely assesses the construct it claims to assess, rather than unintentionally measuring something else."},{"text":"appears to test","correct":false,"explanation":"Merely appearing to assess a construct refers specifically to face validity and does not establish actual validity. A valid measure tests what it claims to test."},{"text":"repeatedly tests","correct":false,"explanation":"A measure can consistently assess the wrong construct, so repeated testing concerns reliability rather than validity. Validity asks whether it tests what it claims to test."},{"text":"was designed to test","correct":false,"explanation":"Researchers’ intentions do not guarantee that a measure genuinely assesses its target construct. Validity depends on whether it actually tests what it claims to test."}]},{"id":"3e5305d1-304e-4f6c-ae8b-6abcbbb6f51c","cardType":"basic","points":2,"front":"Why can tight control reduce ecological validity?","back":"Artificial settings may not reflect everyday behaviour.","mcqOptions":[{"text":"Artificial settings may not reflect everyday behaviour.","correct":true,"explanation":"Strictly controlled laboratory conditions can differ substantially from normal life. Participants may therefore behave differently, limiting how well findings generalise to everyday settings."},{"text":"Artificial settings may not reflect scientific precision.","correct":false,"explanation":"Scientific precision is generally increased, not reduced, by tight control. Ecological validity falls when an artificial setting fails to reflect everyday behaviour."},{"text":"Artificial settings may not reflect random allocation.","correct":false,"explanation":"Participant allocation is an aspect of experimental design rather than the realism of behaviour. Ecological validity is reduced when artificial settings do not reflect everyday behaviour."},{"text":"Artificial settings may not reflect researcher expectations.","correct":false,"explanation":"Researcher expectations concern investigator effects, not whether findings represent real life. Tight control can reduce ecological validity because artificial settings may not reflect everyday behaviour."}]},{"id":"a5577e13-dad1-4e98-b046-c4cc8de47222","cardType":"basic","points":2,"front":"Why is good control of variables a strength of experiments?","back":"It helps isolate the IV’s effect and supports cause-and-effect conclusions.","mcqOptions":[{"text":"It helps isolate the IV’s effect and supports cause-and-effect conclusions.","correct":true,"explanation":"Controlling extraneous variables reduces alternative explanations for changes in the DV. This makes it more reasonable to attribute observed effects to the IV and infer causation."},{"text":"It helps isolate the DV’s effect and supports reversed-causality conclusions.","correct":false,"explanation":"Control does not demonstrate that the DV determines the IV; that reverses the intended causal direction. It isolates the IV’s effect and supports cause-and-effect conclusions."},{"text":"It helps isolate the IV’s effect and supports correlational conclusions.","correct":false,"explanation":"Correlational conclusions concern associations without manipulated variables, whereas experiments manipulate an IV. Good control isolates the IV’s effect and strengthens cause-and-effect conclusions."},{"text":"It helps isolate extraneous effects and supports confounding-variable conclusions.","correct":false,"explanation":"Good control does not show that extraneous variables caused the outcome; it aims to remove their influence. This isolates the IV’s effect and supports causal conclusions."}]},{"id":"a03f9dde-a4a6-467f-bd5b-124a267b7a6c","cardType":"basic","points":2,"front":"Why did Loftus & Palmer’s standardised procedure strengthen their study?","back":"Speed estimate differences were more likely due to verb wording.","mcqOptions":[{"text":"Speed estimate differences were more likely due to verb wording.","correct":true,"explanation":"Participants experienced the same film and procedure, while the critical verb varied between conditions. Differences in estimated speed could therefore be attributed more confidently to verb wording."},{"text":"Speed estimate differences were more likely due to film length.","correct":false,"explanation":"The film’s length was standardised rather than systematically varied between conditions, so it cannot explain their differing estimates. The manipulated difference was the wording of the critical verb."},{"text":"Speed estimate differences were more likely due to actual car speed.","correct":false,"explanation":"The collision shown was identical across wording conditions, so actual vehicle speed did not produce the between-group difference. The changing factor was the verb used in the question."},{"text":"Speed estimate differences were more likely due to viewing instructions.","correct":false,"explanation":"Viewing instructions were kept consistent as part of the standardised procedure, so they were not the systematic difference between conditions. The critical variation was verb wording."}]},{"id":"e1f86e3d-2b6f-4159-ad0f-78cad7a127d8","cardType":"basic","points":2,"front":"Why can manipulating variables raise ethical issues?","back":"It may require deception, stress or concealment of the true aim.","mcqOptions":[{"text":"It may require deception, stress or concealment of the true aim.","correct":true,"explanation":"Manipulating an independent variable may involve misleading participants, exposing them to psychological discomfort, or withholding the study’s true purpose, raising concerns about informed consent and protection from harm."},{"text":"It may reduce ecological validity, realism or generalisability of the findings.","correct":false,"explanation":"Reduced realism and generalisability are methodological limitations rather than ethical issues. The ethical concern is that manipulation may require deception, cause stress, or conceal the study’s true aim."},{"text":"It may introduce demand characteristics, bias or confounding into the results.","correct":false,"explanation":"Demand characteristics, bias and confounding primarily threaten the validity of findings, not participants’ ethical treatment. Ethical issues arise when manipulation requires deception, stress or concealment of the true aim."},{"text":"It may make replication, standardisation or measurement of variables more difficult.","correct":false,"explanation":"Replication, standardisation and measurement concern the reliability and design of research rather than research ethics. Manipulation raises ethical issues when it involves deception, stress or concealment of the true aim."}]}]}],"examCountdown":{"examDate":"2027-05-18","paperLabel":"Paper 1"},"heading":"Variables","title":"Variables Flashcards","topbar":{"backHref":"/a-level/psychology/aqa/flashcards"},"topicSidebar":"$L37"}]}],"topicId":"231459f9-8d4b-51fc-a5d3-5da4bfdf1da0","walled":"$L38"}],"$L39","$L3a"]