Keywords
AI use in education
teachers
predictors
gender
age
teaching experience
level of study
How to Cite
Abstract
Artificial Intelligence (AI) is increasingly transforming education by providing teachers with innovative tools to improve teaching and learning. However, the extent to which teachers adopt AI varies, raising questions about whether background characteristics influence these differences. This study investigated the role of teacher demographic factors in the adoption of AI tools for academic purposes among in-service teachers receiving postgraduate education in a Ghanaian university. Drawing on the Technology Acceptance Model (TAM) and Diffusion of Innovation (DOI) theory, the study examined gender, age, teaching experience, and level of study as potential predictors of AI use. A quantitative cross-sectional survey design was adopted, with data collected from 104 conveniently sampled postgraduate teachers through a structured questionnaire. Data analysis employed t-test, Pearson correlation, and multiple linear regression. Findings showed that level of study was the strongest positive predictor of AI adoption, while teaching experience negatively influenced adoption. Gender, professional rank and age exhibited no significant associations with AI use. The study concludes that advanced academic demands promote AI uptake, whereas reliance on traditional practices may hinder experienced teachers. It recommends leveraging postgraduate programmes as centers of innovation while offering inclusive professional development that supports all teachers regardless of gender or age.
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