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Abstract
Artificial intelligence (AI) is increasingly transforming educational practice by supporting personalized learning, intelligent tutoring, automated assessment, and data-driven instruction. However, the successful integration of AI in mathematics instruction depends largely on educators’ acceptance and readiness to adopt these technologies. This study examined the influence of barriers and enabling factors on lecturers’ acceptance of AI and investigated the effect of teacher acceptance on AI integration in mathematics instruction among Ghanaian Colleges of Education. Guided by the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the study employed a quantitative cross-sectional survey design involving 230 mathematics lecturers. Data were analyzed using Structural Equation Modeling (SEM) with AMOS. The findings revealed that barriers negatively influenced teacher acceptance of AI (β = -0.430, p < .001), whereas enabling factors positively influenced teacher acceptance (β = 0.469, p < .001). Teacher acceptance was also found to significantly predict AI integration in mathematics instruction (β = 0.665, p < .001). The study concludes that reducing implementation barriers and strengthening enabling conditions are critical for promoting AI adoption in mathematics education. The findings provide practical implications for teacher education, institutional leadership, and educational policy aimed at fostering effective AI integration in Ghanaian Colleges of Education.
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References
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