Optimization of Assessment Tools for Course Syllabi Based on a CRM Model and a Genetic Algorithm

Abstract

This paper proposes a genetic algorithm method for optimizing assessment tool funds (ASTF) in Economics based on the CRM model to fully cover competency requirements with ASTF elements. The relevance of this study lies in the growing number of experts working in the development and use of higher education training standards noting the transformation of the higher education paradigm in the current context. The scientific novelty of this study lies in the fact that it bridges the research gap in addressing the optimization of processes for fully covering competency requirements with ASTF elements. The practical significance is that this method will be widely applied in practice, and, in the future, the development of the educational process will experience a transformative nature based on the use of a combination of GitHub and AI.