There are several ways in which research can be controlled to eliminate extraneous variables.
Random allocation of participants is an extremely important process in research. In order to assess the effect of one variable on another, all variables other than the variable to be investigated need to be controlled. Random allocation greatly decreases systematic error, so individual differences in responses or ability are far less likely to consistently affect results.
Counterbalancing is a method used to deal with extraneous effects caused by order effects that arise when using a repeated measures design. The sample is split in half with one half completing the two conditions in one order and the other half completing the conditions in the reverse order. Eg, the first 10 participants would complete condition A followed by condition B but the remaining 10 participants would complete condition B then A. Any order effects should be balanced out by the opposing half of participants.
Randomisation is used in the presentation of trials to avoid any systematic errors that the order of the trials might present.
Standardisation refers to the process in which procedures used in research are kept the same. Great attention is taken to keep all elements of a procedure identical, so that methods are sensitive to any change in performance. Under these circumstances changes in data can be attributed to the I.V. In addition, it is far more likely that results will be replicated on subsequent occasions when research is standardised, which means that data reflects a meaningful pattern and was not a one-off chance result.
Demand characteristics occur when a participant tries to make sense of the research situation, and as a result changes their behaviour. This distorts results, as a participants might intentionally try to demonstrate what the researcher is investigating, or display the opposite (the screw you effect). Participants sometimes try to present themselves in a positive light rather than producing genuine responses/ behaviours, this is known as social desirability bias.
Investigator Effects occur when the presence of the investigator themselves affects the outcome of the research. Eg. during an interview the participants might feel self-conscious or might be influenced by behavioural cues from the researcher (nodding, smiling, frowning etc.).
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