Corpus-Based Mapping of Lexical Disparities within Receptive and Productive Skills in ESP Contexts

Abstract

This study investigates the receptive-productive vocabulary Lexical Disparities among 287 intermediate ESP learners from four academic domains: Engineering, Computer Science, Medical Sciences, and Business. Employing a mixed-methods, corpus-driven design, it integrated corpus analysis of learner production, receptive and productive tests, and stimulated-recall interviews. Results revealed a substantial gap: learners recognized 77.3% of target items on average but accurately produced only 21.6% in spontaneous writing and speech. A mixed-effects logistic regression identified key predictors of productive use, including word frequency (OR=2.32), dispersion (OR=1.51), collocational strength (OR=1.33), and modality (written > spoken, OR=1.71). Crucially, technical terms showed a severe productive bottleneck, exacerbated for learners in Medical Sciences and Business. Qualitative analysis revealed this gap is driven by retrieval failure, collocational uncertainty, and strategic avoidance due to "register anxiety." The findings underscore that the receptive-productive divide is not merely a knowledge deficit but a complex interplay of lexical, cognitive, and affective factors. The study concludes by advocating for production-oriented pedagogical interventions in ESP that systematically bridge this gap through structured output, collocational practice, and activities designed to build lexical confidence.

Keywords

• English for Specific Purposes
• Corpus Analysis
• Learner Corpora
• Lexical Disparities
• Lexical Acquisition
• Receptive Skills
• Productive Skills

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