Journal of Educational Evaluation for Health Professions

Review

Components of the item selection algorithm in computerized adaptive testing: Kyung (Chris) Tyek Han; J Educ Eval Health Prof. 2018;15:7. Published online March 24, 2018; DOI: https://doi.org/10.3352/jeehp.2018.15.7

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Computerized adaptive testing (CAT) greatly improves measurement efficiency in high-stakes testing operations through the selection and administration of test items with the difficulty level that is most relevant to each individual test taker. This paper explains the 3 components of a conventional CAT item selection algorithm: test content balancing, the item selection criterion, and item exposure control. Several noteworthy methodologies underlie each component. The test script method and constrained CAT method are used for test content balancing. Item selection criteria include the maximized Fisher information criterion, the b-matching method, the astratification method, the weighted likelihood information criterion, the efficiency balanced information criterion, and the KullbackLeibler information criterion. The randomesque method, the Sympson-Hetter method, the unconditional and conditional multinomial methods, and the fade-away method are used for item exposure control. Several holistic approaches to CAT use automated test assembly methods, such as the shadow test approach and the weighted deviation model. Item usage and exposure count vary depending on the item selection criterion and exposure control method. Finally, other important factors to consider when determining an appropriate CAT design are the computer resources requirement, the size of item pools, and the test length. The logic of CAT is now being adopted in the field of adaptive learning, which integrates the learning aspect and the (formative) assessment aspect of education into a continuous, individualized learning experience. Therefore, the algorithms and technologies described in this review may be able to help medical health educators and high-stakes test developers to adopt CAT more actively and efficiently.

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Research Article

Exploration of examinees’ traits that affect the score of Korean Medical Licensing Examination: Mi Kyoung Yim; J Educ Eval Health Prof. 2015;12:5. Published online March 16, 2015; DOI: https://doi.org/10.3352/jeehp.2015.12.5

30,228 View
167 Download
2 Crossref

Abstract PDF

Purpose
It aims to identify the effect of five variables to score of the Korean Medical Licensing Examinations (KMLE) for three consecutive years from 2011 to 2013.
Methods
The number of examinees for each examination was 3,364 in 2011 3,177 in 2012, and 3,287 in 2013. Five characteristics of examinees were set as variables: gender, age, graduation status, written test result (pass or fail), and city of medical school. A regression model was established, with the score of a written test as a dependent variable and with examinees’ traits as variables.
Results
The regression coefficients in all variables, except the city of medical school, were statistically significant. The variable’s effect in three examinations appeared in the following order: result of written test, graduation status, age, gender, and city of medical school.
Conclusion
written test scores of the KMLE revealed that female students, younger examinees, and first-time examinees had higher performances.

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