Artificial Intelligence-Driven Instruction and Classroom Technology Utilization in Relation to Learners’ Engagement

Learners’ engagement, AI-driven instruction, and classroom technology utilization are increasingly recognized as essential components of modern teaching and learning that influence how effectively students participate, interact, and achieve learning outcomes. This study examined the relationships among these variables in selected elementary schools in the Oroquieta City. A descriptive-correlational research design was employed, involving 120 elementary school teachers selected through purposive sampling based on specific inclusion criteria, including teaching level, experience with AI or technology use, and willingness to participate. Three validated, reliability-tested researcher-made questionnaires were used to gather data, with Cronbach’s alpha indicating acceptable internal consistency. Data were analyzed using descriptive statistics, and Pearson’s r correlation to determine relationships and predictive effects among variables. Findings revealed that both AI-driven instruction and classroom technology utilization were implemented at a high level, while learners were highly engaged across behavioral, emotional, cognitive, and social dimensions. However, correlation analysis showed that most relationships between AI-driven instruction and learners’ engagement, as well as classroom technology utilization and learners’ engagement, were not statistically significant, except for a weak significant relationship between automated feedback and emotional engagement. The study suggests that while technology and AI are highly implemented in classrooms, their direct impact on learner engagement may depend more on pedagogical application than mere usage.