Teaching Reading in English as a Foreign Language: A Systematic Literature Review of Recent Approches (2020-2025)
Keywords:
educational technology, EFL reading, extensive reading, learning strategies, reading comprehension, systematic literature reviewAbstract
Teaching reading in English as a Foreign Language (EFL) remains a central concern in applied linguistics, with ongoing developments in methodology and technology shaping instructional practices. Recent studies emphasized not only comprehension but also learner autonomy, critical literacy, and engagement through varied pedagogical approaches. This study aimed to synthesize research evidence from the last five years (2020–2025) to identify effective strategies for teaching EFL reading, highlight emerging trends, and examine challenges and implications for classroom practice. A systematic literature review (SLR) was conducted following PRISMA 2020 guidelines. Ten peer-reviewed studies were analyzed, focusing on research design, instructional interventions, and outcomes. The review categorized the studies into five dominant approaches: extensive reading, metacognitive strategy instruction, collaborative learning, flipped classroom models, and problem-based learning. The review found that strategy-based instruction and technology-enhanced methods significantly improve reading comprehension and learner autonomy. Collaborative and flipped learning approaches further enhance engagement, critical thinking, and motivation. However, challenges remain in sustaining learner interest, adapting methods to different contexts, and effectively integrating digital tools. The findings suggested that EFL educators should adopt a balanced pedagogical framework that integrates strategy training, extensive reading opportunities, and interactive technologies. For curriculum designers and policymakers, the review highlights the need for context-sensitive instructional designs. Future research should expand longitudinal studies and explore the impact of emerging technologies such as AI-driven reading platforms.
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This study is based on secondary data (published articles) and does not include original datasets.
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Copyright (c) 2025 Nurdani Yulian Ahmad (Author)

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