DYNAMIC NEEDS ANALYSIS IN ESP: INTEGRATING TRADITIONAL APPROACHES AND AI-DRIVEN LABOR MARKET ANALYTICS
DOI:
https://doi.org/10.31110/2616-650X-vol13i8-010Keywords:
needs analysis, ESP, artificial intelligence, dynamic professions, curriculum design, labor marketAbstract
The article examines the issue of updating needs analysis in English for Specific Purposes (ESP) teaching within rapidly evolving professional domains, such as IT, digital marketing, and biotechnology. In traditional approaches, needs analysis is treated as a one-time procedure that aligns curricula with the current requirements of employers and students. However, the accelerated pace of labor market transformations quickly makes such results outdated, reducing the effectiveness of ESP courses and weakening learner motivation. The study emphasizes the necessity of continuous and cyclical needs analysis that integrates conventional methods (such as questionnaires, interviews, focus groups, and task analysis) with the advanced potential of artificial intelligence and big data analytics. Particular attention is given to the use of AI algorithms for monitoring job advertisements, identifying emerging professional competencies, forecasting skill demands, and recognizing interdisciplinary abilities required in a globalized economy. A conceptual model of “dynamic needs analysis” is proposed, consisting of three levels: (1) systematic collection of feedback from learners and instructors; (2) AI-driven labor market analysis and competence mapping; (3) flexible curriculum adaptation and timely syllabus redesign in response to identified changes. The findings demonstrate that such a model ensures the relevance of ESP programs, improves students’ professional readiness, and strengthens graduates’ competitiveness on the international labor market. The practical significance of the research lies in the development of a methodological framework that enables higher education institutions to create adaptive, future-proof curricula responsive to the challenges of digitalization and global integration. Future research should focus on elaborating evaluation algorithms for the effectiveness of dynamic needs analysis and on comparing its outcomes across different professional domains.
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