Computational thinking (CT), a powerful problem-solving tool, knowledge acquisition optimization, and crucial skill required to engage successfully in the rapidly evolving 21st century, has been increasingly embedded into higher learning and K-12 education curricula across the globe. Since CT incorporation into English as a foreign language (EFL) education is new, the increasing research in this field remains fragmented. This study systematically reviewed 22 empirical studies published from 2015 to 2024 to provide a deeper understanding of the features and trends of CT inclusion in EFL classrooms. Employing a hybrid thematic analysis–constant comparative method across multiple databases, I mapped six EFL focus areas—academic writing, creative writing, reading, vocabulary, grammar, dialogue learning, and sentence structure—and analyzed the distribution of CT skills and cognitive-load levels. Findings demonstrate consistent, positive impacts of CT integration on learner outcomes, with academic writing leading research due to its alignment with high-load CT components such as abstraction and algorithm design. A gap analysis reveals limited teacher involvement and four main barriers: knowledge gaps, time constraints, inadequate professional development, and nascent beliefs. The article ends with some targeted recommendations for policymakers, English educators, and future research.
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