Digital Gamification and AI-driven Feedback Mechanisms in Enhancing EFL Speaking Skills
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Abstract
Cultivating authentic oral proficiency in university-level English as a Foreign Language (EFL) programs remains an uphill battle. In typical tertiary settings, instructors face a difficult dilemma: oversized classes severely restrict the time any single student can spend speaking, while high levels of Foreign Language Classroom Anxiety (FLCA) discourage learners from taking communicative risks in front of their peers. Although Computer-Assisted Language Learning (CALL) has introduced digital gamification to boost student engagement and Artificial Intelligence (AI) to evaluate speech, these two innovations are almost always implemented in isolation. This paper addresses that gap by presenting a practical, integrated pedagogical framework that merges gamified task design with real-time feedback powered by Automated Speech Recognition (ASR). Grounded in the complementary lenses of Self-Determination Theory, Stephen Krashen’s Affective Filter Hypothesis, and Merrill Swain’s Pushed Output Hypothesis, the framework shows how private, AI-mediated rehearsal spaces can help lower psychological barriers while keeping students motivated through structured game mechanics. By shifting routine phonetic drills, repetition exercises, and immediate structural feedback to an interactive digital environment outside class hours, educators can reclaim valuable seminar time for meaningful, face-to-face communicative discourse. Finally, the paper offers concrete guidelines for curriculum developers looking to adopt this hybrid model in modern ELT higher education.
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References
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