Using Computational Thinking to Enhance Problem-Solving in English for Specific Purposes Classrooms

In the evolving landscape of English for Specific Purposes (ESP) education, integrating computational thinking (CT) offers a systematic approach to addressing the cognitive and analytical challenges posed by technical texts. This study investigates the impact of CT strategies—decomposition, pattern recognition, and abstraction—on enhancing ESP learners’ reading comprehension and problem-solving skills. A classroom action research (CAR) framework was employed with second-semester management and engineering students at Universitas Bumigora. A mixed-methods approach combined pre- and post-tests, classroom observations, and reflective journals to measure outcomes and capture qualitative insights. The results revealed significant improvements, with reading comprehension scores rising from 59% to 79% and problem-solving scores increasing from 59% to 80.1%. Large effect sizes (Cohen’s d > 1.1) underscored the efficacy of CT strategies. Qualitative findings highlighted increased student confidence, effective use of decomposition and pattern recognition, and the transferability of skills to other contexts. However, challenges with abstraction persisted, indicating a need for additional scaffolding and instructional support. These findings demonstrate the potential of CT to bridge linguistic and analytical gaps in ESP education. Future research should explore longitudinal impacts and expand the application of CT across diverse ESP fields and teaching methodologies.