Artificial Intelligence Integration for Improving Students’ Learning Outcomes and Motivation - Roys Qaribilla Roys Qaribilla (STIT Fatahillah, 2026)
The integration of Artificial Intelligence (AI) into education has increasingly influenced modern teaching and learning practices. However, the implementation and effectiveness of AI in secondary school settings have not been widely investigated. This research seeks to analyze the influence of AI-supported learning on students’ academic achievement and learning motivation. The study applied a mixed-methods approach using a quasi-experimental design involving 60 eleventh-grade students who were separated into experimental and control groups. Data collection was conducted over four weeks through pre-tests, posttests, and structured questionnaires. Quantitative data were processed using t-test analysis, while qualitative responses were interpreted through thematic analysis. The results reveal that students who participated in AI-assisted learning demonstrated higher academic performance and greater engagement compared to those in conventional learning environments. In addition, the use of AI encouraged more interactive and personalized learning experiences, which positively affected students’ motivation. These findings suggest that AI has considerable potential to improve educational quality and support individualized instruction in secondary education. Therefore, this study provides valuable insights into the role of AI as an innovative tool for increasing the effectiveness of teaching and learning processes in schools