Abstract
Skill gap analysis is one of the most important problems in learning management. Using the computerized adaptive testing provides the effective way to solve this problem and allows adapting the test to the examinee’s ability level. This paper presents an adaptive testing model that integrates hierarchy of knowledge and skills of subject domain and difficulty of the test items. This combination of testing features allows using the presented model for criterion-referenced testing. The following algorithms on the base of adaptive testing model have been developed: starting point selection, item selection, test termination criterion, skill gap assessment. Implementation of these algorithms in the learning management system allows testing the student’s knowledge and skills in specific subject domain purposefully and consider the different ability levels. Developed adaptive testing model and algorithms are applied for testing the basic knowledge and skill gaps in subject domain of variables declaration in C programming language.
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Litovkin, D., Zhukova, I., Kultsova, M., Sadovnikova, N., Dvoryankin, A. (2014). Adaptive Testing Model and Algorithms for Learning Management System. In: Kravets, A., Shcherbakov, M., Kultsova, M., Iijima, T. (eds) Knowledge-Based Software Engineering. JCKBSE 2014. Communications in Computer and Information Science, vol 466. Springer, Cham. https://doi.org/10.1007/978-3-319-11854-3_9
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DOI: https://doi.org/10.1007/978-3-319-11854-3_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11853-6
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