GENERATIVE AI FOR CONTENT CREATION IN EDUCATION: TAILORING LEARNING MATERIALS TO INDIVIDUAL NEEDS - Roni Subhan; Syarifatul Hayati Zarfi; Pong Krit (Al-Hijr: Journal of Adulearn World, 2026)
Growing diversity in learner characteristics, educational backgrounds, cognitive abilities, and learning preferences has increased the demand for adaptive instructional materials capable of supporting personalized learning experiences. Rapid advances in Generative Artificial Intelligence (Generative AI) provide new opportunities to automate educational content creation while tailoring learning resources to individual learner needs, although questions concerning instructional quality, pedagogical effectiveness, and responsible implementation remain unresolved. This study aimed to examine the effectiveness of Generative AI for developing personalized educational content and to evaluate its contribution to teaching and learning within higher education. A mixed-methods sequential explanatory design was employed, integrating quantitative evidence from learning analytics, standardized academic assessments, instructional quality measures, and technology acceptance surveys with qualitative data collected through interviews, classroom observations, reflective journals, and instructional document analysis. Findings revealed that AI-generated personalized learning materials significantly improved academic achievement, learner engagement, creativity, self-regulated learning, instructional quality, learning satisfaction, and course completion when supported by educator supervision and curriculum alignment. Qualitative evidence further demonstrated that adaptive content generation strengthened learner autonomy, instructional flexibility, and educational accessibility while emphasizing the continuing importance of human judgment, ethical oversight, and pedagogical expertise. Results indicate that Generative AI functions most effectively as a collaborative instructional design partner rather than a replacement for educators. Human-centered implementation supported by responsible governance and evidence-based instructional design provides a sustainable pathway for advancing personalized education across diverse learning environments.