TOWARDS RESPONSIBLE AI-ASSISTED TEXTBOOKS: ACCEPTANCE AND ENABLERS AMONG AFRICAN SCIENCE EDUCATORS
DOI:
https://doi.org/10.35631/IJMOE.829018Keywords:
Attitude toward Use (ATU), Facilitating Conditions (FC), Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Technology Acceptance Model (TAM)Abstract
Education is being reshaped by the rapid diffusion of generative AI tools, yet educators’ acceptance of integration of generative AI into science textbooks development and use, particularly among African educators, remains underexplored. This study, grounded in the Technology Acceptance Model (TAM) examined the acceptance of AI-enabled practices in science textbooks among 100 educators from seven African nations participating in the 2025 Third Country Training Programme (TCTP). Using a 5-point Likert survey, the research tested perceived ease of use (PEOU), perceived usefulness (PU), attitudes toward use (ATU), and facilitating conditions (FC). The instrument showed high internal consistency (Cronbach’s α = .898; overall M = 3.31, SD = 0.69). The results indicated broadly positive acceptance; notably, PU emerged as the most influential determinant of attitudes, outweighing PEOU. Structural equation modelling supported all hypothesised paths: FC → PEOU (β = 0.628, p < .001) and FC → PU (β = 0.696, p < .001) were significant; both PEOU (β = 0.516, p = .042) and PU (β = 1.578, p = .002) predicted ATU, with PU the strongest driver; and FC exerted an indirect effect on ATU via PEOU (β = 0.324, p = .020). A clear “capability gradient” emerged: educators reported stronger knowledge than production-grade capacity to embed coding/simulations and AI steps into textbook workflows. Theoretically, the findings proven that improving facilitating conditions, such as reliable infrastructure and structured training, can convert tentative readiness into sustained and habitual AI integration within textbook ecosystems.
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