This study explored a conceptual framework for personalized instruction using cloud-based learning tools in K-12 education. Despite ongoing digital transformation and the widespre adadoption of one-to-one device initiatives in South Korea, the framework of data-driven personalized instruction and its effectiveness remain underexplored in real classroom contexts. A quasi-experimental design was employed to compare cognitive and affective outcomes between personalized and traditional instruction groups in ninth-grade mathematics. While no statistically significant difference was observed in post-test cognitive achievement scores between the two groups, the experimental group demonstrated significantly higher interest and value perception toward mathematics, particularly among lower-achieving students. These findings underscore the potential of cloud-based personalized instruction to enhance affective learning outcomes and learner engagement. This research contributes to the practical application of personalized instruction frameworks and highlights the need for continued development of integrated platforms and teacher support systems to realize the full potential of personalized learning in digitally enhanced educational environments. 

Keywords : Instructional Design, Personalized Instruction, Cloud-based Learning Environment, K-12