Design and Implementation of a Unified Digital Educational Platform Leveraging Artificial Intelligence and Phonological Instruction to Enhance Reading Competence
Year: 2026
Type: conference-paper
Abstract: Reading-related learning difficulties pose persistent challenges for children despite normal intellectual ability and often require instructional approaches beyond conventional literacy teaching. This study aims to design, develop, and evaluate a unified digital educational platform that integrates artificial intelligence and phonological instruction to improve reading competence among children with reading difficulties. The study employed a Research and Development (R&D) methodology using the Four-D model consisting of Define, Design, Develop, and Disseminate stages. The application integrates optical character recognition (OCR) and text-to-speech (TTS) technologies with a phonics-based learning approach to support reading, writing, spelling, and assessment activities. Validation was conducted through material expert review, media expert evaluation, beta testing, and field trials in two elementary schools involving 30 students aged 7 to 15 years. Expert validation results showed high feasibility, with average scores of 4.35 from material experts and 4.4 from media experts on a five-point Likert scale, categorized as very worthy. Beta testing produced an average user response score of 4.75. Experimental results indicated a significant improvement in learning outcomes, with mean scores increasing from 58 on the pretest to 86 on the posttest in the experimental group, compared to an increase from 56 to 77 in the control group. Statistical analysis confirmed normal data distribution and homogeneity, with no significant pretest differences between groups. These findings demonstrate that AI-supported phonics-based digital learning platforms are effective in improving literacy outcomes for children with reading-related learning difficulties.
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7212191968