A Hybrid Decision Support Model Based on AHP–VIKOR and EDAS for Evaluating the Effectiveness of Blockchain Education

In recent years, blockchain technology has moved beyond cryptocurrencies and has emerged as a key driver of structural transformation across various industries. The sustainability of this technological shift largely depends on the development of a qualified human capital base and, consequently, on the effectiveness of educational processes. This study aims to prioritize the effectiveness of blockchain education in line with participants’ expectations and to identify strategic solution proposals that can adequately address these expectations. To this end, a hybrid decision-making model was employed, incorporating the Analytic Hierarchy Process (AHP) for weighting the criteria, the Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method for ranking the solution alternatives, and the Evaluation based on Distance from Average Solution (EDAS) technique for validating the results. In addition, the robustness of the proposed model was examined through a sensitivity analysis supported by Monte Carlo simulation. The findings indicate that C ₂ – Hands-on Learning and Project Experience represents the highest-priority expectation of the participants, while A ₂ – Scenario-Based Learning Approach is identified as the most effective strategy to meet this expectation. These results highlight the critical role of practice-oriented scenarios grounded in real-world problems in transforming theoretical knowledge into practical competence within blockchain education. By integrating the AHP–VIKOR–EDAS methods into a unified framework, this study addresses a methodological gap in the literature and provides a rational decision support mechanism for instructional designers.