A conceptual framework for multi-component summative assessment in an e-learning management system

The article presents a conceptual framework for the design, implementation, and analysis of multi-component summative assessment systems in an electronic educational environment. A universal model is proposed, based on a four-level hierarchy – meta-meta-model, meta-model, model, and actual assessment system. Various structures and assessment components are examined, including Bloom’s taxonomy, higher- and lower-order thinking skills, theory and practice, and the use of fuzzy logic and artificial intelligence. The processes of modeling, configuration, usage, and system analysis are described, along with the roles of the main participants—administrator, author and learner. The use of generative artificial intelligence for the automated creation of test questions is also explored. The system aims to enhance transparency, objectivity, and effectiveness of assessment in digital learning environments, offering practical solutions for modern higher education.

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Publication Details

Journal
Frontiers in Education
Published
2025-09-16
DOI
https://doi.org/10.3389/feduc.2025.1656092
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00

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article

A conceptual framework for multi-component summative assessment in an e-learning management system

Silvia Gaftandzhıeva, George Pashev, Stanka Hadzhikoleva, Emil Hadzhikolev
Frontiers in Education
Intelligent Tutoring Systems and Adaptive Learning
article

A conceptual framework for multi-component summative assessment in an e-learning management system

Silvia Gaftandzhıeva, George Pashev, Stanka Hadzhikoleva, Emil Hadzhikolev
article en

Abstract

The article presents a conceptual framework for the design, implementation, and analysis of multi-component summative assessment systems in an electronic educational environment. A universal model is proposed, based on a four-level hierarchy – meta-meta-model, meta-model, model, and actual assessment system. Various structures and assessment components are examined, including Bloom’s taxonomy, higher- and lower-order thinking skills, theory and practice, and the use of fuzzy logic and artificial intelligence. The processes of modeling, configuration, usage, and system analysis are described, along with the roles of the main participants—administrator, author and learner. The use of generative artificial intelligence for the automated creation of test questions is also explored. The system aims to enhance transparency, objectivity, and effectiveness of assessment in digital learning environments, offering practical solutions for modern higher education.

Frontiers in EducationVol. 10
Plovdiv University (BG)
European Commission
Openalex Percentile: Top 87%
Intelligent Tutoring Systems and Adaptive Learning
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A conceptual framework for multi-component summative assessment in an e-learning management system — Silvia Gaftandzhıeva, George Pashev, et al. · Frontiers in Education (2025) | TGRS Research Map | TGRS