Abstract

This study developed and validated a scale to measure pre-service teachers’ acceptance, readiness, and intention to use Artificial Intelligence (AI) in teaching English. The scale was grounded in three complementary theoretical frameworks: the Unified Theory of Acceptance and Use of Technology (UTAUT) for acceptance, Social Cognitive Theory (SCT) and Constructivist Learning Theory for readiness, and the Theory of Planned Behavior (TPB) for intention. An initial pool of 35 items was generated from established theories and relevant literature. Following face and content validation by six experts, two items were removed based on the Content Validity Index, resulting in a 33-item draft instrument. The scale was then administered to 652 pre-service teachers enrolled in B.Ed. and M.Ed. programmes across six states in India. Item purification led to the deletion of two additional items, producing a final 31-item scale. Exploratory Factor Analysis on one half of the sample and Confirmatory Factor Analysis on the other half supported a clear three-factor structure comprising acceptance, readiness, and intention. The model demonstrated satisfactory psychometric properties, including strong factor loadings, substantial explained variance, acceptable model fit indices, and high internal consistency reliability (overall Cronbach’s alpha = 0.915). The validated scale offers a comprehensive and reliable instrument for assessing how future teachers perceive and prepare for AI integration in English language teaching. It also provides a useful basis for teacher education institutions, curriculum designers, and policymakers to identify training needs and design targeted interventions for meaningful AI integration in language education.

Keywords

Artificial Intelligence, English, India, Pre-Service Teachers, Scale Development, Validation,

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References

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