QUANTIFYING PERSONALIZATION: A MULTIVARIABLE STUDY OF INDIVIDUALIZED TEACHING PLAN EFFECTIVENESS
Received: 04th December 2025, Revised: 11th December 2025, Accepted: 15th December 2025, Date of Publication: 17th December 2025
DOI:
https://doi.org/10.20319/pijtel.2025.93.184203Keywords:
Individualized Teaching Plan, Personalized Learning, Instructional Adaptation, Data-Driven Pedagogy, Learning OutcomesAbstract
Education systems around the world are moving away from traditional teacher-centered methods toward learner-centered approaches that prioritize inclusion, personalization, and measurable growth. However, turning these ideals into consistent and sustainable teaching practices remains a challenge for many educators. This study introduces an evidence-based framework for creating and implementing Individualized Teaching Plans (ITPs) that bridge this gap. It combines theoretical insights, empirical data, and statistical analysis to uncover the factors that most significantly contribute to student success. Drawing from 63 international studies published between 2018 and 2024, nine key instructional parameters that support effective ITPs were identified. In addition, 30 real-world student cases were analyzed alongside the perspectives of 30 education experts to evaluate how these parameters influence academic progress. A multivariable regression analysis revealed that instructional adaptation, goal clarity, review frequency, and assessment regularity have the strongest positive effects on learning outcomes. When teaching is both personalized and guided by data-driven practice, it shows a moderate-to-strong impact on achievement (g = 0.61; R² = 0.72). The paper concludes by presenting a nine-factor ITP model designed for global use—one that highlights the importance of adaptive instruction, reflective planning, and educational equity as essential pillars for improving learning experiences for all students.
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