This article describes a solution for learning how to build the method of frequency characteristics of the control object. Nowadays, the level of competencies required in the work of a modern engineer is becoming higher and higher, and the more difficult it is to provide the necessary level of knowledge and skills using only the traditional approach. This problem can be solved by implementing automated learning systems that will relieve teachers, reach more students, and unify the quality of work. The subject of the research is the possibility of building a certain abstract system that will be able to provide complex skills for students in an automatic mode. The basis for this research is a complex task that requires various skills from the learner. As a system that requires well-developed skills, we can cite the system of construction of the frequency characteristics of the control object. This work studied the methods for building such systems, as well as to study the learning ability of students and for extracting the most frequent and possible errors of students. The goal is to design and run a system that allows the student to acquire skills in constructing the frequency characteristics of an object. This work allows use of one of the possible methods for implementing such a task, as well as identifying the most common problems at the stage of learning this technique and the most successful method to prepare the system for use. In the process of the task, the following results were obtained: student errors were identified and classified. Based on the signal-parametric approach to the diagnosis of faults in dynamic systems, mathematical diagnostic models were created, that allow the system to identify classes of errors by comparing the calculation results of the student and the calculation results of the system. The peculiarities of the application of the proposed diagnostic models are presented. The intelligent tutor system is developed and used in practical classes on "Theory of automatic control" by third-year students of the National Aerospace University “Kharkiv Aviation Institute”.
Although all advantages of a standard approach to teaching students new skills, we are increasingly faced with problems such as the inability to pay an equal amount of attention to many students, to work through and unambiguously highlight all possible problems and mistakes, to close knowledge gaps. Also, all these difficulties are becoming even more urgent given the current state of affairs in the world and the global transition to an online learning format. As a possible solution to the problem, one can consider the creation of independent intelligent systems capable of taking on a part of the load of teachers and automatically participating in the process of teaching students. The subject of research in this article is the process of analyzing the steps for solving algebraic equations using the Lobachevsky-Graeffe-Dandelen method. The goal is to model the process of solving algebraic equations and to identify all possible steps, difficulties and problems in solving such problems. Objective: development of a system capable of monitoring the execution of all necessary steps for a given solution, identifying and classifying possible student mistakes in the process of mastering the skill and work them out. In the process of the task, the following results were obtained: one possible solution for learning to solve an n-degree algebraic equation using the Lobachevsky-Greffe-Dandelen method has been described. On the basis of the signal-parametric approach to diagnostics of faults in dynamic systems the mathematical diagnostic models are created which allow detecting classes of errors by comparing the results of Student's calculations and the results of system calculations. The features and possible difficulties of application of the proposed diagnostic models are presented. An intelligent self-contained tutor system was developed and integrated into the work at practical classes on "Theory of Automatic Control" by 3rd year students of the National Aerospace University.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.