Artificial Intelligence (AI) Aided Learning and Academic Performance of Students in Sirawai National High School: Basis for Instructional Development
Abstract
This study examined the extent of Artificial Intelligence (AI)-aided learning and its relationship with the academic performance of Junior High School students at Sirawai National High School during School Year 2024–2025. Anchored in Cognitive Load Theory, Social Cultural Theory, and the Technology Acceptance Model, the study considered learning abilities, problem-solving skills, and critical-thinking abilities as dimensions of AI-aided learning. A quantitative descriptive-correlational design was employed with 247 purposively selected Grades 7–10 students who had experience using AI tools, particularly ChatGPT and Cici. Data were collected using a modified standardized 15-item questionnaire with a five-point Likert-type scale and a Cronbach’s alpha of 0.928. Frequency, percentage, weighted mean, mean average, and Pearson Product Moment Correlation Coefficient were used for data analysis. AI-aided learning was experienced to a high extent overall (M = 3.91), including learning abilities (M = 4.00), problem-solving skills (M = 3.96), and critical-thinking skills (M = 3.83). Students obtained a mean academic grade of 86.52, indicating very satisfactory performance. No significant differences in AI-aided learning were found according to sex, age, and ethnicity, while a significant difference was identified according to grade level. Learning abilities and problem-solving skills were not significantly related to academic performance, whereas critical-thinking skills showed a very weak negative but significant relationship (r = -0.204, p = 0.001). Overall AI-aided learning also showed a very weak negative but significant relationship with academic performance (r = -0.152, p = 0.017). The study recommends appropriate AI integration and teacher training on effective and ethical AI use. It supports SDG 4—Quality Education and SDG 9—Industry, Innovation and Infrastructure through responsible educational technology integration. Its sustainability impact lies in supporting educational, technological, and institutional decision-making that balances AI assistance with independent learning, critical thinking, and problem-solving.