2026· International journal of research and innovation in social science· Vol 10, pp. 15086-15097· 0 citations
TL;DR
Findings revealed that students demonstrated a moderate level of AI utilization, recognizing its relevance for academic tasks but showing limited confidence and motivation for deeper engagement, suggesting that while AI contributed positively, it was not the sole determinant of success.
Abstract
This study investigated the relationship between artificial intelligence (AI), resources and technology, and academic achievement among global learners using a quantitative correlational research design. The respondents consisted of 279 Grade 7 students from 12 schools in the Pendergast Elementary School District, Avondale, Arizona, USA, representing diverse cultural and academic backgrounds. Data were gathered through a structured questionnaire covering demographic profiles, AI utilization, and technology experiences. Findings revealed that students demonstrated a moderate level of AI utilization, recognizing its relevance for academic tasks but showing limited confidence and motivation for deeper engagement. Resources and technology experiences were generally high, with strong access to basic digital platforms but limited exposure to advanced tools. Academic achievement was satisfactory overall, with comparable performance across demographic groups. Results indicated no significant differences in AI utilization, resources, or achievement based on age, though gender influenced AI engagement. Importantly, a statistically significant but weak relationship existed between AI utilization and academic achievement, suggesting that while AI contributed positively, it was not the sole determinant of success. Resources and technology experiences showed no significant impact on achievement, implying that instructional quality and learner related factors played a greater role.
It is suggested that AI use may be associated with specific learning outcomes but should not be viewed as a direct predictor of overall learning performance, and proposed an AI-supported teaching enhancement strategy to promote responsible and effective AI use in learning.
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