Method of adaptive control structure learning based on model of test's complexity

Pasichnyk, Roman; Melnyk, Andriy; Pasichnyk, Natalia; Turchenko, Iryna

doi:10.1109/idaacs.2011.6072858

Cited by 14 publications

(1 citation statement)

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“…Adaptive testing allows to accurately determine the level of learning of material, avoids the use of excessive number of test tasks, but requires a very large number of test tasks in the base set. Also, adaptive testing requires the mandatory definition of a number of parameters of each test task (complexity, semantic relation with the educational material) for its adaptive use [21]. The field of application of parameterized tests is mainly automation of formation of mathematical tasks.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Method for Adaptive Semantic Testing of Educational Materials Level of Knowledge

Mazurets

Barmak

Krak

et al. 2021

Lecture Notes in Computational Intelligence and Decision Making

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The article considers the method that allows to calculate the estimation of knowledge level of educational materials by using indicators of semantic importance of key terms for adaptive selection of test tasks in testing. Each test task allows to purposefully check the level of knowledge of separate semantic units of educational materials -semantic terms (words, phrases). It is assumed that increasing the depth of learning of educational material semantic content has the effect of learning less semantically important units of educational materials. Semantic terms are related to the semantic structure of educational material in the form of rubricational system. Test tasks are related to fragments of educational material content, the knowledge level of which they test. In the process of testing, the level of knowledge of each of semantic structure elements of the educational material is consistently adaptively determined, and the final grade is calculated based on these results. As a result of adaptive selection of test tasks, their maximum possible diversity in the final set is reached, because following criteria are considered: test task has not been used yet, relevant fragment of educational content has not been checked, test tasks of corresponding type were used the least, the test task does not contain less important semantic units. The developed method of adaptive semantic testing of knowledge level of educational materials makes possible to use different algorithms for starting testing (regressive, progressive, medianic, etc.) and different algorithms for knowledge level estimation (average, absolute limit, etc.). Applied investigations of the effectiveness of the developed method in comparison with the traditional algorithm for selecting test tasks established, that testing speed increased an average of 20.53% faster test, and to determine the level of knowledge required the use of an average of 19.33% fewer test tasks.

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Section: Introduction and Literature Reviewmentioning

confidence: 99%