Question

What are the threats to external validity? How could each threat affect you as a researcher? Come up with a research sample for each threat to external validity. What are some methods to increase external validity?

Answer 1

• Threats to external validity are any factors within a study that reduce the generalisability (or generality) of the results.
• Four of the main threats to external validity that I or any researcher may face in the research are discussed with associated examples. These include: (a) selection biases; (b) constructs, methods and confounding; (c) the 'real world' versus the 'experimental world'; and (d) history effects and maturation.
• As a master's level dissertation student, it is common to use other university students as the main participants in my research. Whilst this provides for a much more accessible sample, it will inevitably result in selection bias, reducing the ability to make generalisations to a wider population, which is unlikely to be so heavily made up of university students.
• For my research taking a construct like intelligence which is a broad concept and can be studied from various perspectives is not the apt choice and so more specific contructs are needed for the research purpose.Since experiments cannot take into account all of the different ways that a concept can be perceived and measured, it will only be possible to make generalisations from the results within the confines of the operational definition provided by me for my concept. By operational definition, we mean the construct I decided to study from some broader concept (i.e., how I perceived a concept), and the specific way I decided to measure that construct (i.e., the variables I used to represent the construct)
• Using a single method to measure a given construct known as mono-method bias, it threatens the construct validity of the measurement procedure I may use.
• When making generalisations, whether to a wider population, or across populations, treatments, contexts/settings, or time, we are making generalisations from the experimental world to the real world. For example,In one of my researches learning effect took place which posed a threat to external validity.Learning effects, also known as practice effects or carry-over effects resulted in increased post-test performance i.e., higher scores on the dependent variable because participants became familiar with some aspect of the experiment.
• Random sampling methods can help increase external validity i.e. all members have an equal chance of being included in the sample.To improve external validity, many investigators focus on the sample, and try taking larger, more varied samples, to try make the findings more applicable to the wider population.Additionally ecological validity is improved by carrying out the investigation in different, more realistic settings to try make the findings more relevant to everyday life.