CONTROL OF VARIABLES

SPECIFICATION:

• Variables: manipulation and control of variables, including independent, dependent, extraneous, confounding; operationalisation of variables.

• Control: random allocation and counterbalancing, randomisation and standardisation.

• Demand characteristics and investigator effects.

Internal validity threats that can affect the accuracy and reliability of research findings.

• EXTRANEOUS VARIABLES

• CONFOUNDING VARIABLES

• DEMAND CHARACTERISTICS

• INVESTIGATOR EFFECTS

• OBSERVER BIAS

• THE HAWTHORNE EFFECT

• SOCIAL DESIRABILITY BIAS

• STANDARDISATION

In research, especially within the field of psychology, controlling variables is crucial to ensure the validity of the experiment's results. Two types of variables that researchers need to be cautious of are extraneous variables and confounding variables. Although they might seem similar, they have distinct roles and implications for research.

EXTRANEOUS VARIABLES

Extraneous variables are all variables other than the independent variables that could affect the outcome of the experiment. These are not of interest to the research question but could influence the dependent variable if not controlled. The key with extraneous variables is that they are identified by the researcher and are controlled or accounted for, to ensure that any effects on the dependent variable can be attributed solely to the independent variable.

EXAMPLES:: If you're studying the effect of a new teaching method on student learning outcomes (dependent variable), an extraneous variable could be the students' initial interest level in the subject. This interest could affect how well students perform, irrespective of the teaching method. To control this, researchers might measure students' initial interest and account for it in their analysis, or they might try to equaliSe interest levels across groups through selection or matching.

DEMAND CHARACTERISTICS: Guessing the aim of the experiment and acting in non-genuine way. A term referring to the tendency of some people to work harder and perform better when they are participants in an experiment. Individuals may change their behavior due to the attention they are receiving from researchers rather than because of any manipulation of independent variables. Participants are therefore not acting in non-genuine waySolution: placebo and single blind (if applicable) and do not reveal aim or hypothesis by using presumptive or prior general consent.

THE HAWTHORNE EFFECT The Hawthorne effect is a type of reactivity in which individuals modify an aspect of their behavior in response to their awareness of being observed. The effect was discovered in the context of research conducted at the Hawthorne Western Electric plant; however, some scholars feel the descriptions are apocryphal.

SOCIAL DESIRABILITY BIAS: Participants wishing themselves to be seen a positive desirable light and therefore not acting in non-genuine/ valid way. Slot box or anonymity.

INVESTIGATOR EFFECTS: Investigator effects result from the effects of a researcher’s behaviour and characteristics on an investigation. E.g., they may be attractive, a different class or intimidating.  Participants may therefore not act in genuine/ valid way. Try to match investigator if possible on class, ethnic, origin, age. Train to not act intimidating.

INVESTIGATOR BIAS Investigators unintentionally influencing the participant’s behaviour by suggesting which way they want the results to turn out. Solution: double and single blind.

OBSERVER BIAS: Observer using own subjective view. Solution: Operationalise definition

OTHER EXAMPLES:

• Questionnaires that don’t test what they say they do. For example does an IQ test measure intelligence or education? If the latter than IQ tests are invalid.

• Testing participants in different conditions at different times of day. Time of day affects performance.

• Testing participants in different conditions in different settings (hotter room, more attractive or comfortable room. Again this can affect performance making results invalid.

• Not randomly allocating participants to conditions

• Not counterbalancing

CONFOUNDING VARIABLES

Confounding variables, on the other hand, are a type of extraneous variable that was not controlled for and ends up varying systematically with the independent variable. This makes it impossible to determine whether changes in the dependent variable were caused by the independent variable or the confounding variable. Confounding variables compromise the internal validity of an experiment because they offer an alternative explanation for the observed relationship between the independent and dependent variables.

EXAMPLES: Consider an experiment to determine if a new cognitive-behavioral therapy technique (independent variable) reduces anxiety levels (dependent variable). If the therapy sessions are always conducted in a relaxing room with soft lighting, while the control group sessions are in a less comfortable setting, the setting could be a confounding variable. The difference in anxiety levels could be due to the therapy technique or the environment where the therapy is conducted, making it difficult to isolate the effect of the therapy technique alone.

KEY DIFFERENCES

• Control: Extraneous variables are identified and controlled by the researcher, whereas confounding variables are not controlled and can obscure the relationship between the independent and dependent variables.

• Impact on Validity: While both can affect the outcome, confounding variables directly threaten the internal validity of the experiment by providing an alternative explanation for the results.