• Aleksandr A. Baymakov, Irkutsk state agrarian university named after A.A. Ezhevsky (Molodezhny settlement, Irkutsk region, Russia)
• Yaroslav M. Ivanyo, Irkutsk state agrarian university named after A.A. Ezhevsky (Molodezhny settlement, Irkutsk region, Russia)
• Nina I. Fedurina, Irkutsk state agrarian university named after A.A. Ezhevsky (Molodezhny settlement, Irkutsk region, Russia)

This article presents the results of a study aimed at developing an "Educational Program Management" module as part of the university's electronic information and educational environment (EIEE). The module's mathematical and algorithmic support enables forecasting accreditation monitoring indicators, thereby improving the quality of educational management. The study is based on an analysis of long-term data from 20 educational programs at Irkutsk State Agrarian University. The scientific novelty of this work lies in the systematization of data collection, storage, and processing processes, as well as the development of specialized forecasting algorithms adapted to the specific statistical parameters of monitoring indicator time series. Unlike existing developments, the proposed algorithms are implemented as a practical tool integrated into the university's EIEE. To forecast indicators such as the average Unified State Exam score, the percentage of successful completions, and the percentage of employed graduates, a combination of methods was used, including correlation and regression analysis, expert assessment methods, and probabilistic modeling based on a three-parameter gamma distribution. It is proposed to differentiate the accuracy of forecast assessments based on the level of preparation of applicants. The developed module was tested on real data, and the forecast accuracy was assessed. A retrospective forecast of key accreditation indicators was performed, the values of which were compared with actual data. The average relative forecast error was 12.8% for the average Unified State Exam score, 18.8% for the percentage of successful completions, and 6.7% for the percentage of employed graduates. The obtained results demonstrate the practical applicability of the module for the early assessment of educational programs' compliance with accreditation requirements and the formation of informed management decisions.

accreditation, monitoring, educational program, electronic information educational environment, modeling, management

2026-03-05