IB DP Psychology: Approaches to researching behaviour – Study Guide

Psychologists cannot see thoughts, motives or feelings directly, so they rely on research methods that turn behaviour into evidence. This topic asks you to understand how studies are designed, why one method suits one question better than another, how participants are chosen, how data are analysed, and what makes a study credible and ethical. It also supports everything else in the course, because every theory you learn rests on research that you need to evaluate.

Where this fits in the specification

Approaches to researching behaviour runs through the whole IB Diploma Programme Psychology course rather than sitting in one approach. You use it when evaluating studies in the biological, cognitive and sociocultural approaches and options, and it is the basis of the internal assessment, in which you carry out a simple experimental study. Questions may ask you to describe a method, explain why a design is suitable, identify strengths and limitations of a study in a scenario, or discuss ethical considerations. Check the current guide for the precise required content at each level.

Quantitative and qualitative research

Quantitative research collects numerical data, such as reaction times or test scores, and analyses it statistically. It is good for testing hypotheses and comparing groups. Qualitative research collects non-numerical data, such as words in an interview, and looks for themes and meanings. It is good for exploring experiences in depth and generating new ideas. The two can be combined (mixed methods).

Experiments

An experiment manipulates an independent variable (IV) and measures its effect on a dependent variable (DV) while controlling other variables. There are several kinds:

• True (laboratory) experiment: participants are randomly allocated to conditions in a controlled setting. It gives the strongest evidence of cause and effect but may lack ecological validity.
• Field experiment: the IV is manipulated in a natural setting. Control is lower and realism higher.
• Natural experiment: the IV changes naturally, for example a policy change, and the researcher does not control it.
• Quasi-experiment: the IV is a characteristic participants already have, such as age or gender, so participants cannot be randomly allocated.

Designs can be independent samples (different people in each condition), repeated measures (the same people in every condition) or matched pairs. Independent samples avoid order effects but risk participant variables; repeated measures control participant variables but allow practice and fatigue effects, which can be reduced by counterbalancing.

A good hypothesis is a testable prediction. A null hypothesis says there is no effect, and an alternative hypothesis states the predicted difference or relationship. A confounding variable is an uncontrolled variable that varies with the IV and may explain the result.

Correlational studies

A correlational study measures the relationship between two variables without manipulating either. A positive correlation means that both increase together, and a negative correlation means that as one rises the other falls. Correlation does not show causation, because a third variable may cause both, or the direction may be the opposite of what is assumed.

Qualitative methods

• Observation records behaviour as it occurs, either in naturalistic or controlled settings. It can be participant or non-participant, and overt or covert. Observers need clear categories and, ideally, more than one observer to check reliability.
• Interviews can be structured, semi-structured or unstructured. They give rich data but depend on the skill of the interviewer, and participants may give socially desirable answers.
• Focus groups gather a small group to discuss a topic, which can reveal shared views but may be dominated by one person.
• Case studies are in-depth investigations of an individual, group or event, often using several methods over time. They give detailed insight into rare cases but are hard to generalise.

Sampling

The target population is the group the researcher wants to draw conclusions about, and the sample is the subset who take part. Common techniques are:

• Random sampling: everyone has an equal chance of selection. It reduces bias but is hard to achieve.
• Stratified sampling: the sample reflects the proportions of subgroups in the population.
• Opportunity (convenience) sampling: people who are available. It is quick but can be biased.
• Volunteer (self-selected) sampling: people respond to an advertisement, which can mean a more motivated sample.
• Purposive sampling: participants chosen for specific characteristics, common in qualitative work.
• Snowball sampling: participants recruit others, useful for hard-to-reach groups.

A larger and more representative sample generally supports generalisation.

Ethical considerations

Researchers follow ethical guidelines to protect participants. Key principles are informed consent, protection from harm, confidentiality, the right to withdraw, debriefing after the study and avoiding unjustified deception. Studies with children, or with vulnerable people, need extra care such as parental consent. Many institutions use an ethics committee to check proposals. Ethical issues often involve balancing the possible benefit of knowledge against the risk to participants, and in animal research there are separate rules on welfare.

Credibility, bias and generalisation

• Validity is whether a study measures what it claims to. Internal validity means the IV caused the change in the DV, and external validity means the findings apply beyond the study (to other people, settings and times). Ecological validity is realism of the setting and task.
• Reliability is consistency: would the same result be found again?
• Researcher bias includes expectations affecting how data are collected or interpreted. Participant bias includes demand characteristics, social desirability and the placebo effect. Blind and double-blind procedures reduce these.
• In qualitative research the equivalent of validity is credibility, and the equivalent of generalisation is transferability. They are strengthened by triangulation (using several methods, researchers or data sources), reflexivity (the researcher reflecting on their own influence), rich description and checking findings with participants.

Descriptive statistics

Descriptive statistics summarise data. The mean is the sum divided by the number of values; the median is the middle value; the mode is the most frequent. The range is the highest value minus the lowest, and the standard deviation measures how far values typically are from the mean, with a small value meaning the data are clustered close to the mean. Inferential statistics are used to decide whether a result is likely to be due to chance, and whether you need them depends on the level you take.

Worked example

Ten participants try to recall words from a list after a learning task. Their scores are 12, 15, 9, 14, 11, 13, 15, 10, 12 and 14.

1. Sum: 12 + 15 + 9 + 14 + 11 + 13 + 15 + 10 + 12 + 14 = 125. Mean = 125 / 10 = 12.5.
2. Ordered scores: 9, 10, 11, 12, 12, 13, 14, 14, 15, 15. The fifth and sixth values are 12 and 13, so the median = (12 + 13) / 2 = 12.5.
3. Modes: 12, 14 and 15 each appear twice, so there is no single mode (the data are multimodal).
4. Range = 15 - 9 = 6.
5. Standard deviation (sample): deviations from 12.5 squared are 0.25, 6.25, 12.25, 2.25, 2.25, 0.25, 6.25, 6.25, 0.25 and 2.25, giving a total of 38.5. Dividing by 9 gives 4.28, and the square root is about 2.07.
6. Interpretation: the mean and median are the same, so the distribution is fairly symmetrical, and the standard deviation of about 2.1 shows that typical scores sit about two words either side of the mean. The sample is small and opportunity sampled, so you cannot generalise from it.

Common mistakes

• Saying a correlation proves that one variable causes another.
• Confusing independent and dependent variables, or listing a confounding variable as the IV.
• Describing a sampling technique without saying how it affects representativeness.
• Using the words reliability and validity interchangeably.
• Applying quantitative terms such as generalisability to qualitative research without naming credibility and transferability.
• Forgetting to link ethical issues to a specific study.

Exam technique

When a question gives a scenario, use it. Name the method and variables from the scenario, and suggest the improvement that fits that study, such as counterbalancing in a repeated measures design. For evaluate questions give a balanced judgement, and for suggest questions propose a sensible idea with a reason. Define terms briefly and accurately before using them.

Check your understanding

1. What is the difference between a true experiment and a quasi-experiment? In a true experiment participants are randomly allocated to conditions; in a quasi-experiment the IV is an existing characteristic.
2. Name one way to reduce order effects in a repeated measures design. Counterbalancing.
3. Why does correlation not prove causation? A third variable may explain both, or the direction of the relationship may be reversed.
4. What is triangulation? Using more than one method, researcher or data source to strengthen credibility.
5. What does debriefing involve? Explaining the true aims after the study, addressing concerns and offering the chance to withdraw data.
6. Find the mean of 4, 7, 7, 10 and 12. 40 / 5 = 8.
7. Give one limitation of opportunity sampling. The sample may not be representative, so generalisation is limited.

Frequently asked questions

What is the difference between a true experiment and a quasi-experiment? In a true experiment, participants are randomly allocated to conditions. In a quasi-experiment, the independent variable is a characteristic participants already have, such as age or gender, so random allocation is not possible.

What are credibility and transferability in qualitative research? Credibility is the qualitative equivalent of validity, and transferability is the equivalent of generalisation. Both are strengthened by triangulation, reflexivity, rich description and checking findings with participants.

What does standard deviation show? Standard deviation measures how far values typically are from the mean. A small standard deviation means the data are clustered close to the mean.

How is approaches to researching behaviour used in IB Psychology? It runs through the whole course: you use it to evaluate studies in the core approaches and options, and it is the basis of the internal assessment, a simple experimental study.