Artificial Intelligence and Decision Making
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Artificial Intelligence and Decision Making, 2015, Issue 4, Pages 51–61 (Mi iipr337)  

Intelligent systems and technologies

Cognitive tools in learning and testing systems based on mixed diagnostic tests

A. E. Yankovskayaa, M. E. Semenovb, A. V. Yamshanovc, D. E. Semenovb

a Tomsk State University of Architecture and Building
b Tomsk Polytechnic University
c Tomsk State University of Control Systems and Radioelectronics
Abstract: E-learning systems and assessment of learning quality on these systems are briefly described. In order to improve the learning quality and the accuracy of his assessment is the use of different visualization tools, including cognitive. The approach based on mixed diagnostic tests and cognitive tools for creating the hybrid intelligent e-learning and testing system is given. This approach allows reducing cost and time of learning with improving of learning quality. The paper describes cognitive tools developed by us and their applying in learning systems, namely, 2- and 3-simplices, sector diagram with additional dependencies DiADep, circle diagram Target. Applying of these tools allows increasing assessment accuracy of learning quality, revealing new dependencies at learning process, investigating dynamic of learning, modeling influence of different factors on effectively of learning process, assessing of learning results of students. Future investigations are discussed.
Keywords: E-learning systems, learning and testing systems, mixed diagnostic tests, cognitive tools, DiADep diagram, Target diagram, estimation of learning quality.
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: A. E. Yankovskaya, M. E. Semenov, A. V. Yamshanov, D. E. Semenov, “Cognitive tools in learning and testing systems based on mixed diagnostic tests”, Artificial Intelligence and Decision Making, 2015, no. 4, 51–61
Citation in format AMSBIB
\Bibitem{YanSemYam15}
\by A.~E.~Yankovskaya, M.~E.~Semenov, A.~V.~Yamshanov, D.~E.~Semenov
\paper Cognitive tools in learning and testing systems based on mixed diagnostic tests
\jour Artificial Intelligence and Decision Making
\yr 2015
\issue 4
\pages 51--61
\mathnet{http://mi.mathnet.ru/iipr337}
\elib{https://elibrary.ru/item.asp?id=25461407}
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