BEYOND RECOGNITION: TOWARD A TASK-BASED FRAMEWORK FOR DEVELOPING PRODUCTIVE VOCABULARY IN MOBILE-ASSISTED LANGUAGE LEARNING

Abstract

Mobile-assisted language learning (MALL) has become one of the most extensively researched areas in vocabulary pedagogy, with recent systematic reviews and meta-analyses converging on a consistent conclusion: mobile tools reliably support vocabulary gains. Yet a closer reading of this literature reveals a persistent asymmetry. Most MALL research, and most MALL tools themselves, are built around tasks that develop receptive knowledge — recognizing a word’s form and meaning — while productive knowledge, the ability to retrieve and correctly use a word in speech or writing, develops more slowly and is measured far less often. This asymmetry is particularly consequential in English for Specific Purposes (ESP) contexts, where the communicative goal of instruction — writing a professional email, negotiating a deal, delivering a presentation — is inherently productive. This paper synthesizes findings from recent systematic reviews, meta-analyses, and empirical studies on mobile-assisted vocabulary learning to examine why this receptive bias persists, and proposes a conceptual Recognition-to-Production (R2P) framework for auditing and redesigning MALL vocabulary tasks. The framework organizes mobile vocabulary tasks into three tiers — recognition, controlled production, and free production — and maps common mobile affordances onto each tier. Pedagogical implications are discussed with particular attention to ESP instruction in higher education, and directions for empirical validation of the framework are outlined.