SIMULATION-BASED COMPETENCY MODEL (SBCM): A CONCEPTUAL–METHODOLOGICAL FRAMEWORK FOR ENGINEERING EDUCATION

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Authors: Asila Olimovna Abdullaeva
Cited by: 0

Abstract

Engineering education is undergoing profound transformations driven by digitalization, simulation technologies, and the expansion of virtual laboratories. These trends are accompanied by a shift toward outcome-based and competency-based frameworks, particularly within internationally recognized accreditation systems. However, methodological integration between simulation-based learning environments and competency models remains insufficiently developed, resulting in weak operational connections between program learning outcomes, simulation scenarios, and assessment procedures. The purpose of this conceptual–methodological study is to introduce a Simulation-Based Competency Model (SBCM) that functions as an integrative framework linking competency domains to simulation designs, learning activities, and assessment indicators in engineering education. The model is grounded in the theoretical traditions of competency-based and outcome-based education, performance-based assessment, and simulation-driven instructional design. SBCM is represented as a four-layer architecture comprising competency, simulation, activity, and assessment levels, and it includes an operational mapping procedure for translating learning outcomes into simulation-based tasks and performance criteria. Methodologically, the study contributes to improving alignment between engineering accreditation frameworks and simulation-driven digital training. Limitations involve technological and organizational constraints associated with implementation. Future research should focus on empirical validation of SBCM, integration with AI-supported assessment tools, and adaptation for simulation-driven engineering training environments.

Fields of Study & Subjects

Engineering Education and Curriculum Development Experimental Learning in Engineering Engineering Education and Pedagogy

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 January 2026