Аnalytical computer-integrated system for monitoring stem education outcomes
DOI:
https://doi.org/10.33216/1998-7927-2026-301-3-80-86Keywords:
STEM education, computer-integrated system, educational analyticsAbstract
The article addresses automation of STEM education outcome monitoring processes under conditions of educational environment digitalization and increasing educational data volume. Modern STEM approaches involve integration of learning outcomes across disciplines, as well as project-based and research activities, which complicates objective assessment using traditional, mainly manual and fragmented monitoring methods. Insufficient systematization of educational data processing reduces analysis efficiency and limits effectiveness of decision-making in education.
The study aims to develop and investigate approaches to designing an automated STEM education outcome monitoring information system based on computer-integrated technologies. A computer-integrated system concept is proposed, ensuring centralized data collection, storage, processing, and analysis, as well as generation of generalized learning outcome indicators.
The paper examines system structural organization, information flows, and automated educational data processing algorithms. Application of STEM education outcome analysis models is proposed, enabling integral assessment of learning achievements and supporting decision-making processes. Practical significance of the proposed approach lies in the possibility of implementing a computer-integrated monitoring system in secondary and higher education institutions to improve assessment objectivity, increase analysis efficiency, and enhance STEM education process management.
Such systems support more meaningful analysis of student learning outcomes, enable instructors to respond promptly to changes in the educational process, and facilitate development of individualized learning trajectories.
Particular attention is given to implementation of a demonstration web-based analytical module prototype, confirming functionality of the proposed normalization and integral evaluation algorithm for STEM education outcomes and demonstrating its applicability within modern digital educational environments.
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