Design of Individual Learning Trajectory Based on Mixed Diagnostic Tests and Cognitive Graphic Tools

Anna E. Yankovskaya, Yury N. Dementyev, Danil Yu. Lyapunov, and Artem V. Yamshanov


learning and testing intelligent system, pattern recognition, mixed diagnostic tests, fuzzy logic, blended learning, cognitive graphic tool


In this paper we discuss the relevance of students’ computer-based testing, as well as the currently existing approaches for the control of learning and training within the scope of blended learning. Construction of mixed diagnostic tests, representing a compromise between unconditional and conditional components, in order to develop students' knowledge monitoring in electrical engineering is proposed. The authors suggest a technique for optimal mixed diagnostic tests construction based on the expert knowledge of the subjects. Decision-making is carried out by means of fuzzy logic, threshold function and cognitive graphic tools. One of the useful outcomes of mixed diagnostic tests is the courses learning curve design for each individual student. The developed approach is applied for the “Power Electronics” discipline to construct students’ learning trajectory and define their further ways of personal development in the field of electrical engineering.

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