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TEACHING PRACTICES OF GRADE 8 SCIENCE TEACHERS EMBEDDED WITH AI-DRIVEN ADAPTIVE LEARNING SYSTEM IN SCIENCE INSTRUCTION

📘 Volume 12 📄 Issue 10 📅 October 2026

👤 Authors

Jenny M. Santiago 1 , Sonny De Leon PhD 1
1. Graduate School, Nueva Ecija University of Science and Technology, Cabanatuan City, Nueva Ecija, Philippines,

📄 Abstract

Artificial intelligence (AI) offers opportunities to personalize science instruction, yet evidence regarding teachers’ AI-supported practices and learners’ cognitive engagement remains limited. This study examined Grade 8 Science teachers’ practices embedded with AI-driven adaptive learning systems at Bongabon National High School, Nueva Ecija, during school year 2026–2027. Specifically, it described teachers’ profiles and practices across planning and preparation, classroom environment, instruction, and professional responsibilities, and investigated relationships and differences in respondents’ perceptions. A descriptive survey design with quasi-experimental designation, involved six Grade 8 Science teachers and 499 students. Teacher respondents were covered through complete enumeration, while student respondents were selected through simple random sampling. Questionnaires provided data analyzed using frequencies, percentages, weighted means, t-tests, and Spearman’s rho. Findings indicated that AI-embedded teaching practices were “Always Practiced,” with an overall grand weighted mean of 3.60. Classroom environment obtained the highest combined domain mean (3.64), followed by instruction (3.62), planning and preparation (3.59), and professional responsibilities (3.55). Teachers’ educational attainment showed significant negative relationships with planning and preparation (rho = −0.892) and classroom environment (rho = −0.874), whereas other profile variables showed no significant relationships. Teachers’ and learners’ perceptions did not differ significantly across domains. The study concluded that AI-supported teaching practices were consistently reported and recommended targeted professional development and activities to strengthen comparatively less-practiced areas. These findings may guide context-responsive integration of adaptive learning tools in junior high school Science instruction while supporting reflective teaching practice and student engagement. This supports responsible implementation.

🏷️ Keywords

AI-Driven Adaptive Learning Systems; Cognitive Engagement; Grade 8 Science; Teaching Practices; Descriptive Survey; Educational Technology

🔗 DOI

DOI - (https://doi.org/10.36713/epra29152)

📚 How to Cite:

Jenny M. Santiago, Sonny De Leon PhD , TEACHING PRACTICES OF GRADE 8 SCIENCE TEACHERS EMBEDDED WITH AI-DRIVEN ADAPTIVE LEARNING SYSTEM IN SCIENCE INSTRUCTION , Volume 12 , Issue 10, October 2026, EPRA International Journal of Multidisciplinary Research (IJMR) , Pages: 127 - 131 , DOI: https://doi.org/10.36713/epra29152

🔗 PDF URL

https://cdn.eprapublishing.org/article/1791913234184-19.EPRA 29152.pdf

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