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Maram Almaneea, Imam Mohammad Ibn Saud Islamic University, Saudi ArabiaAbstract
As artificial intelligence becomes increasingly embedded in educational environments, language learning is progressively shifting towards personalised, algorithm-driven models that prioritise efficiency and individualised feedback. While AI-mediated platforms provide expanded access to linguistic input, they may inadvertently reduce opportunities for dialogic engagement, intercultural interaction, and collaborative meaning-making. This concern is particularly relevant in English as a Foreign Language (EFL) contexts such as Saudi Arabia, where English functions as a key medium for global academic and professional participation. This study reconceptualises structured classroom debate as a human-centred pedagogical intervention within AI-augmented language learning environments. Rather than positioning debate solely as a tool for improving speaking proficiency, the study explores its role in cultivating communicative competencies that remain beyond the scope of algorithmic optimisation, including intercultural awareness, perspective-taking, and communicative adaptability. Using a quasi-experimental pretest–posttest control group design, the study examined the impact of integrating a structured debate project into a first-year university Listening and Speaking course on students’ perceived intercultural competence. Findings revealed statistically significant improvements among students who participated in the debate intervention. The results suggest that dialogic, interaction-based pedagogies can help preserve essential relational dimensions of communication in increasingly AI-mediated language learning environments.
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Conference: ECAH2026Stream: Humanities - Teaching and Learning
This paper is part of the ECAH2026 Conference Proceedings (View)
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