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<p>Singapore’s reading education system has significantly evolved, integrating digital technology into reading instruction, which is central to its high performance in international assessments like PIRLS. This study investigates how Reading Instruction Practices (RIP) influence Reading Comprehension Strategies (RCS) and Digital Literacy in Reading Instruction (DLRI) within Singapore’s high-achieving educational system. Using Structural Equation Modeling (SEM) based on 221 observations, the model demonstrated excellent fit indices (CFI = 0.993, TLI = 0.991, RMSEA = 0.072, SRMR = 0.079). Significant paths were found between RIP and RCS (estimate = 0.643, <i>p</i> &lt; 0.001), RIP and DLRI (estimate = 0.411, <i>p</i> &lt; 0.001), and RCS and DLRI (estimate = 0.200, <i>p</i> = 0.041). The model explained 41.4% of the variance in RCS and 31.5% in DLRI, suggesting other factors also influence these outcomes. The findings underscore the need for comprehensive professional development programs that equip educators to integrate digital technologies with traditional reading techniques. Policymakers should allocate resources for professional learning communities and digital infrastructure. Educators must create integrative instructional designs, refine responsive practices, and commit to ongoing professional growth, ensuring the effective use of technology in enhancing reading education. This holistic approach prepares students for the demands of the digital age while maintaining high literacy standards.</p>

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The role of reading instruction practices in enhancing digital literacy and comprehension strategies in Singapore

  • 期刊论文

  • 发表日期：

    2025年11月28日

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  • Pongprapan Pongsophon

摘要

Singapore’s reading education system has significantly evolved, integrating digital technology into reading instruction, which is central to its high performance in international assessments like PIRLS. This study investigates how Reading Instruction Practices (RIP) influence Reading Comprehension Strategies (RCS) and Digital Literacy in Reading Instruction (DLRI) within Singapore’s high-achieving educational system. Using Structural Equation Modeling (SEM) based on 221 observations, the model demonstrated excellent fit indices (CFI = 0.993, TLI = 0.991, RMSEA = 0.072, SRMR = 0.079). Significant paths were found between RIP and RCS (estimate = 0.643, p < 0.001), RIP and DLRI (estimate = 0.411, p < 0.001), and RCS and DLRI (estimate = 0.200, p = 0.041). The model explained 41.4% of the variance in RCS and 31.5% in DLRI, suggesting other factors also influence these outcomes. The findings underscore the need for comprehensive professional development programs that equip educators to integrate digital technologies with traditional reading techniques. Policymakers should allocate resources for professional learning communities and digital infrastructure. Educators must create integrative instructional designs, refine responsive practices, and commit to ongoing professional growth, ensuring the effective use of technology in enhancing reading education. This holistic approach prepares students for the demands of the digital age while maintaining high literacy standards.