AI-powered e-modules for mathematics learning: Impact on elementary school students' mathematical disposition - Fadhilaturrahmi; Ananda, Rizki (Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) Universitas PGRI Mahadewa Indonesia, 2025)
Mathematical disposition is an essential affective aspect that influences students' success in understanding and enjoying mathematics, but it is often neglected in conventional learning approaches. Students' lack of motivation, confidence, and perseverance in mathematics is a fundamental problem in elementary schools. This study aims to analyze the effect of implementing an Artificial Intelligence (AI)-based E-Module on improving the mathematical disposition of elementary school students. A quantitative approach with a quasi-experimental design was used. The sample consisted of 70 fifth-grade students in Pekanbaru who were randomly divided into experimental and control groups. The instrument used was a mathematical disposition test developed based on five leading indicators validated for validity and reliability. The t-test results showed a significant difference between the post-test scores of the experimental and control groups (p < 0.05), with higher mathematical dispositions in the group using AI-based E-Modules. These findings indicate that AI-based learning systems are effective in cognitive aspects and capable of fostering positive attitudes and motivation toward learning among students. The novelty of this study lies in its focus on measuring affective elements within the context of adaptive technology in elementary education. The implications of these findings encourage the integration of AI-based learning that is not only oriented toward academic outcomes but also toward strengthening students' character and mental readiness to face the challenges of 21st-century education.