Quantifying teachers’ readiness for artificial intelligence adoption in education: a mathematical modeling perspective

Quantifying teachers’ readiness for artificial intelligence adoption in education: a mathematical modeling perspective

Abstract We developed a mathematical model based on the classical SEIR (Susceptible–Exposed–Infective–Recovered) framework to predict teachers’ readiness to adopt Artificial Intelligence (AI) in educational settings, with a specific focus on Nigeria. In this context, we reinterpret the compartments...

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Bibliographic Details
Main Authors: Musa Adekunle Ayanwale, Kabir Oluwatobi Idowu, Owolabi Paul Adelana, Sideeqoh Oluwaseun Shosanya, Oluwanife Segun Falebita, Kayode A. Adewale
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Artificial intelligence in education
Teacher readiness
Mathematical modeling
SEIR model
Online Access:https://doi.org/10.1038/s41598-025-08018-x
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https://doi.org/10.1038/s41598-025-08018-x

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