AUTOMATION OF GENERATING VARIANT CONTROL AND MEASUREMENT MATERIALS IN MATHEMATICAL ANALYSIS USING THE COMPUTER ALGEBRA SYSTEM MAPLE

This article addresses the issue of improving the efficiency of preparing test materials (TMM) for the "Function Derivative" section of a mathematical analysis course. The traditional approach to creating assignments and benchmark solutions is labor-intensive, especially when parallel versions need to be created to ensure objective knowledge assessment. The aim of this work is to develop and implement a software algorithm for the automated generation of functions and their derivatives for generating variable TMMs. The Maple computer algebra system was selected as the platform. During the study, the DiffTable procedure was designed and implemented. Its purpose is to automatically parse source mathematical expressions, ana- lytically calculate first- and second-order derivatives, and calculate the numerical values of the resulting expressions at a given point. The procedure produces a structured data table. It can serve both as a basis for handouts and as a reference for verification. The novelty of this approach lies in the creation of an algorithmic task generator that allows users to vary the types of functions and the values of arguments without having to manually recalculate the results. The practical significance of this work is demonstrated by the ability to run the DiffTable procedure multiple times to generate an unlimited number of test variants. This minimizes the likelihood of students copying answers. The proposed method can be adapted to generate multiple-choice tests on other topics in mathematical analysis.

learning automation, assignment generation, test variability, computer algebra systems (CAS), Maple, symbolic computation, function derivative, pedagogical measurements.

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2026-08-17