Test reliability can be defined as the extent to which test scores are not influenced by chance factors (Livingston et al., 2018). Chance factors, in this case, refer to factors that influence the outcome of the test but are not necessarily what the test aims to access and therefore lead to inconsistency in test scores. This inconsistency is referred to as the measurement error and could either be due to examinee-specific factors, test-specific factors, or scoring-specific factors.
Examinee-specific factors are factors that affect the individual examinee and include motivation, concentration, fatigue, momentary lapses of memory among others. Test-specific factors, on the other hand, are the factors that revolve around the test environment and include the chosen set of questions for the test, ambiguous or trick items, and even poor directions. Lastly, scoring-specific factors are factors that revolve around how the test is scored. For instance, the uniformity of scoring guidelines, carelessness and counting, and computational errors ( Heale & Twycross , 2015).
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In an unreliable test, there is little to no difference in the student’s test scores and randomly assigning scores as the scores majorly consist of measurement error. It is therefore necessary to ensure that tests that are administered have good measures of reliability and the scores reflect more than just random error (Hu et al., 2016). Two primary factors are key to improving the reliability of a test. These factors include increasing the length of the test and improving the item quality.
Increasing the length of a test decreases the percentage of measurement error as many items are tested thus limiting the luck-chance factor. However, it is important to ensure that the length is such that the items can be covered within the specified time limit. The intelligence test would therefore have several items that are broad in terms of the subject matter being tested to ensure that the examinee’s intelligence is thoroughly tested. The quality of items also plays a great role in ensuring that the measurement error is kept as low as possible. In this case, high-quality items easily distinguish the examinees with high content mastery from those whose content mastery is not adequate. On top of ensuring that the intelligence test covers a broad spectrum of the content, the test would delve deep into the content and have clear and concise items to fairly bring about the greater distinction among the examinees (Taherdoost, 2016) .
References
Livingston, S. A., Carlson, J., Bridgeman, B., Golub-smith, M., & Stone, E. (2018). Test reliability–Basic concepts. Research Memorandum No. RM-18-01). Princeton, NJ: Educational Testing Service .
Heale, R., & Twycross, A. (2015). Validity and reliability in quantitative studies. Evidence-based nursing , 18 (3), 66-67.
Hu, Y., Nesselroade, J. R., Erbacher, M. K., Boker, S. M., Burt, S. A., Keel, P. K., ... & Klump, K. (2016). Test reliability at the individual level. Structural equation modeling: a multidisciplinary journal , 23 (4), 532-543.
Taherdoost, H. (2016). Validity and reliability of the research instrument; how to test the validation of a questionnaire/survey in research. How to Test the Validation of a Questionnaire/Survey in a Research (August 10, 2016) .
