Improving reading comprehension through a digital and intelligence-based instructional model

Abstrak

Reading comprehension is a crucial component of literacy that significantly impacts students’ academic development across various subjects. However, conventional teaching methods often fail to accommodate the diverse cognitive strengths of learners, leading to disengagement and limited understanding. This study introduces a digital and intelligence-based instructional model designed to enhance reading comprehension among third-grade elementary students. The model integrates visual-spatial and linguistic-verbal intelligences with interactive digital modules to promote more engaging and effective learning. Using a Design and Development research approach, the model was systematically designed, validated by experts, and implemented in five elementary schools. Eight instructional sessions were conducted to examine the practical application and effectiveness of the approach. Data were collected through pre-tests, post-tests, classroom observations, and teacher interviews; however, the sampling techniques used were not clarified. Statistical analysis using paired and independent t-tests revealed significant improvements in students' reading comprehension in the experimental group compared to the control group. Qualitative findings also showed increased student motivation and participation during learning activities. The results suggest that a digital instructional model grounded in learners’ cognitive profiles can substantially support literacy development at the primary level. Future studies are recommended to refine sampling procedures and extend the application across broader educational contexts.