Abstract
This study analyzed educational technology adoption dynamics among university faculty using a four-state compartmental model formulated with ordinary differential equations and computational simulation. Six institutional scenarios were examined over 36 months using reproducible EduAdopt-4D research resources. Deterministic solutions were compared with computationally generated trajectories and 960 Monte Carlo replications; parameter sensitivity and numerical convergence analyses were also performed. At month 36, estimated adoption reached 66.29\% under the integrated intervention scenario, compared with 54.52\% in the baseline scenario and 43.71\% under digital overload. The analyses highlighted the influence of fatigue and recovery mechanisms on sustained adoption. The findings indicate that the proposed approach enables quantitative exploration of faculty technology-adoption transitions and comparison of institutional strategies under explicit assumptions. It offers a reproducible framework for subsequent applications and calibration studies in university settings.
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