Integrating Artificial Intelligence into Adaptive ESP Curriculum Design: Pedagogical Innovations for Specialized Language Learning - Eslam Shehata Ahmed Yacoub (Journal of English for Academic and Specific Purposes (JEASP), 2026)
The rapid expansion of artificial intelligence (AI) in education has renewed scholarly interest in the ways technology can enhance English for Specific Purposes (ESP) curriculum design, particularly in highly specialized fields such as healthcare. The present study investigates the pedagogical impact of integrating AI-driven feedback into an adaptive ESP writing curriculum and examines its effects on learners' acquisition of domain-specific vocabulary and communicative competence. A convergent mixed-methods design was employed: undergraduate healthcare students enrolled in a medical English ESP course were assigned to either an AI-enhanced instructional condition or a traditional instructional condition. Quantitative analyses of pre-test and post-test writing tasks revealed significantly greater gains for the AI-enhanced group in grammatical accuracy, lexical specificity, and overall textual coherence, with these gains corroborated by platform analytics from the Write & Improve system. Qualitative evidence drawn from semi-structured student interviews and faculty observation notes demonstrated strong learner engagement, positive perceptions of the immediacy of AI-generated feedback, and increased confidence in revising specialized texts, alongside concerns regarding the potential for over-reliance on automated feedback. The findings indicate that AI-supported personalization can meaningfully enhance ESP learning outcomes when it is integrated within a pedagogically coherent curriculum. The study contributes empirical evidence to the emerging field of AI-informed ESP research and offers practical implications for the design of adaptive, technology-supported ESP instruction in both professional and academic settings.