Monday, June 27, 2011

Validity, Operational Definition and Triangulation

1. Describe the issue/concept
2. What implication(s) does this have for knowledge gained in the human sciences (how does this issue or concept affect our ability to learn and know things via the human sciences?)

1. The most common definition of validity is epitomized by the question: are we measuring what we think we are measuring? Validity is the extent to which a test measures what it claims to measure. In order for the results of an experiment or test to be published/ applied to human life, they must first be proven to be valid. It is crucial to remember that validity isn’t determined by a single statistic. Instead it is determined by a large collection of research that demonstrates the relationship between the test and the behaviour that it was designed to measure. There are many different types of validity including Internal, External, Conclusion, Construct, Criterion related, and Content validity. Each is with regard to a different way of collecting knowledge for example intelligence tests are one example of measuring instruments that should have construct validity i.e. they use means of statistical analysis of the internal structure of the test, to look at the relationships between different responses to test items. It is well known that the concept of scientific validity, focuses upon the nature of reality and therefore it is an epistemological and philosophical issue as well as a question of measurement. The use of the term ‘validity’ with regard to logic is narrower as it relates to the truth of inferences made from propositions upon which arguments are based and conclusions; drawn. When conducting research scientists draw conclusions from their findings. Often after researching these processes, foredawn conclusions create the basis of the results to arguments that scientists look to solve. As nearly all social research involves measurement or observation of some kind it is a common fact that when we measure or observe something, we are concerned with whether we are measuring truthfully what we are observing, or are demand characteristics causing us to ‘see’ something else. The implications had on our knowledge gained in the human sciences are based around the importance of validity with regard to conducting research. We know that experiments which are conducted within the social science field, desire to measure intangible things e.g. attitudes, behaviours, emotions, and personalities. These rely on processes such as interviewing, physiological analysis etc which in turn need to be valid before they can be publicized.

2. Operational Definition is a procedure agreed upon for the translation of a concept into a measurement of some kind. It expresses how to measure the item being defined using specific details and in its absence many problems can occur. A common example of the use of operational definition surrounds the argument as to how a passenger could decide whether their plane arrived on time? Is it judged by the time of landing which was stated as the arrival time, when the plane stops taxiing or when the first or last passenger leaves the plane? This is why operational definitions must be extremely precisely written to avoid possible variation in interpretations. E.g. to continue with the above example, at what stage could a passenger claim compensation for a ‘late’ flight – here the operational definition will tell us whether in fact the flight was late. Within the realm of human science, operational definition is the transformation of an abstract/ theoretical notion into something fixed, observable and measurable to scientists conducting a research experiment. Without it, data collected may be defective and therefore some things that are overlooked by researchers may be included by others. It is therefore important for scientists to universally share and acknowledge the same bounds created for research and the process of conducting it. Because these bounds are so crucial to the process of measurement they are often very controversial.

3. Triangulation is a technique that aids the validation of data through cross verification from two or more sources. It refers specifically to the application and combination of several research methods surrounding the same concept. Triangulation can be exercised in both quantitative (validation) and qualitative (inquiry) studies. It revolves around the founding of the credibility of qualitative analysis and is an alternate method to traditional criteria such as reliability and validity; making it the most highly favoured method in the social sciences. By including multiple observers, theories, methods, and empirical materials, researchers can hope to overcome the weakness or problems which arise when dealing with only one single method, single-observer or single-theory study. The process of triangulation impacts upon the human sciences, as the technique is most commonly used when researching, using more than two methods/theories/observers/empirical materials, so to be able to double (or triple) check results collected. This is process is called "cross examination” and it extremely important because without a doubt, people are more willing to believe “cross examined” theories/results.  With regard to researching, it can be seen that if an investigator uses only one method, he will naturally presume that his findings are accurate/true. If however, he uses two methods, the results may vary substantially. If he used three different methods he will hope that two out of three methods will produce similar answers. If all three methods produce completely different results/findings then he will know that he needs to reconsider his methods or initial question.   

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