Experimental Research (Variables (Confounding variable: any variable minus…
Behaviours studied by controlling variables, enabling experimenter to isolate one key variable been selected (IV) to observe the effect on another variable (DV). Controlling other confounding variables helps conclude the IV influenced the DV, establishing cause and effect.
Independent Variable IV:
The variable the experimenter manipulates or changes.
Dependent Variable (DV):
The variable that experimenter measures.
When identifying IV and DV, important both
so making clear how IV is manipulated and how the DV is measured. So outlining what pp's will do and how behaviours measured.
any variable minus IV, affecting DV. They can reduce validity of findings. Classified as
Participant variables- age, sex, alertness, intelligence.
Situational variables- time of day, heating, lighting, weather.
Variable that can have effect on the DV but controlled so doesn't become a confounding variable.
used in experiments. Group of pp who aren't exposed to the IV used for comparison with experimental groups.
Way pp's organised into groups is the design.
Where pp's only take part in one condition of experiment.
Strengths- Eliminates order effects because people are only tested once. Improving validity.
Reduces demand characteristics because pp's only tested once so don't see changes in IV. Improving validity.
Weaknesses- Individual differences likely because different people in each condition, yet being compared. Reducing validity of results.
Not as economical in time and resources because collect twice as many people than repeated measures.
Solution- Reduce individual differences if you have a large, representative sample, randomly allocated to conditions.
Repeated Measures Design:
Pp's take part in both/all conditions of experiment.
Strengths- Eliminates individual differences because same pp's are being tested in both conditions (being compared against themselves). Improving validity of results.
Need less pp's because one group gets used twice.
Weaknesses- Order effects likely because people tested twice and can get bored. Reducing validity.
Demand characteristics because pp's being tested twice, figure out what the study is about. Reducing validity.
Solution- Counter-balancing or matched pairs.
Matched Pairs Design:
pp's only take part in one condition but pp's matched on key variable(s) e.g. age, gender, IQ.
Strengths- Individual differences reduced because pp's matched so comparison group should be similar on important characteristics, improving validity. Eliminates order effects because pp's being tested in one condition, improving validity.
Weaknesses- Individual differences still possible because never match pp's on all important characteristics, reduce validity.
Uneconomical time and resources and complicated to carry out because pp's need pre-testing for matching to be done.
Solution- Matched pairs best design- no real solution, repeated measures completely eliminates individual differences.
Experiment conducted under highly controlled conditions, manipulating an IV. Lab is any environment where variables well controlled. Environments usually artificial, allow precise control of variables.
Strengths- High levels of control over confounding variables because carried out in a controlled environment. Therefore allowing cause and effect to be established and so resulting in high internal validity.
Lab experiments easy to replicate because have standardised procedures. So have high reliability.
Weaknesses- Lack ecological validity because they are carried out in artificial environments and participants may not behave naturally. Therefore results can't be generalised to real life situations/behaviour.
Participants may be subject to demand characteristics because may guess what the study is about and change their behaviour. Reducing validity of the findings.
Experiment conducted in natural environment, with manipulation of an IV. Usually unaware they're taking part.
Strengths- High ecological validity because carried out in natural environments and pp's behave naturally. Results can't be generalised to real life situations/behaviour.
Reduce demand characteristics because if pp's don't know they're being studied they can't guess what it's about and change their behaviour. Increasing validity of findings.
Weaknesses- Low levels of control over confounding variables because carried out in natural environment. Reducing internal validity, can't establish cause and effect.
Field experiment difficult to replicate because don't have standardised procedures. Have low reliability.
Where the IV is not manipulated by researcher but occurs naturally. Often natural experiments. Quasi-experiment researcher takes advantage of pre-existing conditions e.g. age, gender, disability, occupation, etc.
Strengths- Allow researchers to investigate areas would otherwise be unavailable to them because investigate areas can't be directly manipulated for practical or ethical reasons.
Weaknesses- Difficult to establish cause and effect because researcher has no control over IV. Therefore reducing internal validity.
Research Question, Aims & Hypotheses
Answerable enquiry into specific concern/issue. Initial step in research project after deciding what you want to study.
overall purpose of study, clearly defined. Broad statements of desired outcomes, or general intentions of research.
Specific prediction about what you expect to happen in your study/research. They test hypotheses and ways to word it.
Alternative Hypothesis- Your prediction of what will happen. Can be one or two tailed.
Null hypothesis- Statement of no difference.
Reliability of Experiments
Factors affecting reliability- Standardisation of procedures (control over environment, task, apparatus/materials, timings, instructions, etc.) Control of variables, field based or lab based, researcher bias.
Improvements- Standardising instruction and procedures so everyone does same thing in experiment. Controlling extraneous variables.
Validity of Experiments
Factors affecting validity- Internal validity: level of control (more controlled more confident). Level of demand characteristics, experimenter bias.
External validity: Setting, Realism of task, Generalisability of sample.
Improvements- Avoid giving hints about purpose of investigation, use single and double-blind designs to avoid demand characteristics and researcher bias, have high levels of control over variables. Carry out research in real life settings and reflects real life experiences.
They're a research method used by psychologists involving manipulation of variables to discover cause and effect. Differing from non-experimental methods involving deliberate manipulation of one variable, trying to keep all other variables constant.