Abstract
In this article, an automated knowledge testing system with adaptive parameters, which assumes the individualization of the training courses and test tasks content designed to control the knowledge of each learner is considered. Existing systems of automated testing of knowledge are considered. The analysis of existing approaches to the organization of adaptive testing is carried out. A system that has the ability to adapt to the level of knowledge of the learner and has the ability to select suitable topics for training is proposed. An algorithm for testing knowledge with the adaptation of the choice of topics depending on the level of knowledge of learner was developed and presented. The influence of the level of complexity of tasks on the criterion of knowledge of students is considered. The results of experimental use of the adaptive testing system and its impact on the level of knowledge control of learner are presented. An adaptive testing model using the apparatus of fuzzy mathematics is considered. The description of fuzzy characteristics of test tasks and functions of determining the level of learner training is proposed.
Published Version
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