Functional Education as a Nexus between Agricultural and Industrial Revolution: An Epidemiological Modeling Approach

Keywords: education, revolution, model, equilibrium points, expenditure, corruption, simulation


Education has been regarded as a major route to economic prosperity. Its potentials, if properly exploited, have the tendency to revolutionize a nation’s productivity, income, and development. [Objetive] In this work, a mathematical model was formulated, and an epidemiological modeling approach was explored to derive the necessary and sufficient conditions for agricultural and industrial transformation in Nigeria in terms of education. The use of mathematics to quantify such a phenomenon is relatively new. [Methodology] Ample mathematics theorems were employed to test for the existence, boundedness, and positivity of the model’s solutions which are basic features of a valid epidemiological model. The model was solved to derive the equilibrium points, and the analytic threshold that governed revolution in industry and agriculture in terms of education was derived. Stability and sensitivity analyses were conducted via the stability theory of nonlinear differential equations and normalized forward sensitivity index, respectively. Simulations were later conducted using the Maple software to validate the analytical results.  [Results] A government expenditure of 25% on education with or without corruption did not make education functional. Also, an increase in expenditure on education to 65% but with corruption of more than 30% retarded functional education. In general, education became functional when government investment in education attained 60%, with corruption levels lower than 20%. [Conclusions] Both the analytical and numerical results linked agricultural transformation and industrial revolution through functional education to massive investment in education and victory over corruption.


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How to Cite
Ayoade, A., & Thota, S. (2023). Functional Education as a Nexus between Agricultural and Industrial Revolution: An Epidemiological Modeling Approach. Uniciencia, 37(1), 1-16.
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