Designing Mahārah al-Kalām Instruction through Speech Act Analysis of Authentic YouTube Video
DOI:
https://doi.org/10.32332/ijalt.v8i01.13263Keywords:
Authentic Video, Deep Learning, Mahārah al-Kalām, Speech ActAbstract
The gap between the functional mandates of KMA Number 450 of 2024 and the prevailing reality of Arabic instruction in madrasahs remains a critical issue. This study aims to analyze speech acts within authentic YouTube videos and utilize them as a foundation for designing Mahārah al-Kalām instruction based on the Deep Learning framework. Employing a descriptive qualitative design, the primary research instrument was the researcher, supported by document analysis guidelines. The corpus comprised 76 spoken utterances extracted from three authentic YouTube videos representing history, health, and popular science genres. These data were analyzed using Searle’s speech act theory and Fullan’s Deep Learning elements. The results showed distinct pragmatic patterns across genres: historical videos were dominated by assertive speech acts for epistemic authority, health videos relied on intimate directives, and popular science videos exhibited linguistic hybridity through expressive acts. Consequently, this study formulates an instructional design integrating four elements: learning partnerships, learning environments, leveraging digital, and pedagogical practices. The implications of this study offer a proposed pedagogical model for Arabic language educators to transition from rigid textbook-bound grammar instruction to dynamic, culturally responsive digital pedagogy, facilitating active student engagement and autonomous learning in the 21st century.
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