Tests and assessments are very important in helping people with learning and understanding human behavior. They involve a highly standardized process that examines an individual’s sensual ability and mental processes (Cohen, Swerdlik & Sturman, 2013). Due to their objective nature, tests and assessments ought to have quality results. The results should be effective and dependable. Some of the most commonly used concepts in tests and assessments are validity and reliability (Cohen et al., 2013). It is important to ensure that the methodologies used to conduct tests and assessments focus on measuring the intended element in a qualitative manner.
Meaning of reliability in testing and assessment
Reliability refers to the ability of the quality of data used in tests and assessments to remain stable and dependable throughout (Long & Johnson, 2000). Reliability influences on the consistency of test results very much. The reason for this is that assessment relies on the quality of data collected. In the context of tests and assessments, concept of quality encompasses the ability of data used to be accurate even when the test is conducted at a different time or given to a different individual from the same sample population.
The reliability of data collected is measured using three approaches, namely test-retest, alternate form method and split-half (Milton, Bull & Bauman, 2011). Test-retest is the commonly used approach and involves administering a similar test to the same group of individuals at different times. Results from both tests are compared to check whether the results are similar or not (Stewart, Turner & Miller, 2012).
Meaning of validity in tests and assessments
Validity in tests and assessments refers to the ability of data collected to be effective in measuring the intended element (Milton et al., 2011). Validity does not allow for deviations in the standards of the data used in tests and assessments. For example, a test can be administered to measure the intelligence of an individual. Such a test can only be considered to be valid if it examines only the individual’s intelligence and ignores other elements. Validity in tests and assessments can be measured using two approaches, namely internal and external (Milton et al., 2011).
Internal validity examines the ability of a test to measure the intended elements in their sample. It focuses on achieving accurate information for the targeted elements and all the others that could be there. On the other hand, external validity examines the possibility of using results from a single test to make an assessment of a larger population from which a sample is sourced (Long & Johnson, 2000). It focuses on examining the effectiveness of samples used in tests to represent their parent population. It assumes that the results gotten from a sample give an indication of what to expect if everyone is tested.
Importance of reliability and validity
Reliability and validity influence tests and assessments in various ways. It is very important to ensure that these two concepts are achieved in every test (Buelow & Hinkle, 2008). As earlier mentioned, reliability has a huge effect on the degree of consistency achieved by test results in terms of their accuracy and dependability. Studies have established that tests and assessments focus on achieving reliability because of various reasons. Reliability helps to ensure that the data used in assessing the performance of individuals is correct, consistent, logical, and covers the element intended to be examined (Buelow & Hinkle, 2008).
Validity also plays a crucial role in tests and assessments. The strictness and effectiveness of the data collected in a test are used in assessing the performance of individuals in the population from which examination samples are sourced. This helps to increase the scope of study for tests, as well as saving time and resources that could have been spent studying the whole population (Buelow & Hinkle, 2008). Validity also influences the consistency of results generated from tests and assessments.
Norming in tests and assessments
In tests and assessments, norming refers to the process of developing statistics describing the location of a distribution for data analysis. These statistics are referred to as norms because they describe the performance of a selected population from the results received out of their samples (Cohen et al., 2013). For example, norming can be used to compare the performance of a class by analyzing the performance of a single student against the average performance. The variables that are subjected to comparison are called norms.
The process involves a number of steps that ought to be followed systematically. Some of the key steps of the process include the identification of a target population, the elements to be examined, the acceptable degree of sampling errors, estimating the sample size, and identification of normative scores (Stewart et al., 2012). The process also involves forming a table, which an analyzer uses to convert raw data into inferred data. Once the data is converted, the analyzer is supposed to document the process that will be used to interpret the normative scores in order to determine the performance (Cohen et al., 2013).
References
Buelow, J.M., & Hinkle, J.L. (2008). Research corner: Why are reliability and validity important to neuroscience nurses? Journal of Neuroscience Nursing, 40(6), 369-372.
Cohen, R.J., Swerdlik, M.E., & Sturman, E.D. (2013). Psychological Testing and Assessment: An Introduction to Tests and Measurements. New York: McGraw-Hill Companies.
Long, T., & Johnson, M. (2000). Riqour, reliability and validity in qualitative research. Clinical Effectiveness in Nursing, 4(1), 30-37.
Milton, K., Bull, F.C., & Bauman, A. (2011). Reliability and validity testing of single-item physical activity measure. British Journal of Sports Medicine, 45(3), 203-208.
Stewart, P.F., Turner, A.N., & Miller, S.C. (2012). Reliability, factorial validity, and interrelationships of five commonly used change of direction speed tests. Scandinavian Journal of Medicine & Science in Sports, 24(3), 500-506.