Artificial intelligence–supported deep learning approaches for enhancing mathematical literacy in elementary teacher education - Rida Fironika Kusumadewi; Nuhyal Ulia; Setyo Wuri Kartika Nugraheni (Jurnal Ilmiah Pendidikan Dasar, 2026)
The low level of mathematical literacy in Indonesia, particularly among PGSD students, highlights an urgent need to strengthen basic education competencies, prompting this study to examine the influence of deep learning supported by Artificial Intelligence (AI) on the mathematical literacy of PGSD students at Sultan Agung Islamic University (Unissula). Using a quasi-experimental One Group Pretest-Posttest design with 20 participants, the study implemented AI-assisted deep learning activities to enhance students’ conceptual understanding and problem-solving skills. The results showed a significant improvement in mathematical literacy, indicated by a significance value of 0.000 between pretest and posttest scores, demonstrating the effectiveness of the instructional approach. Furthermore, the average student response score of 83.375 reflected strong engagement and a positive learning experience throughout the intervention. These findings suggest that integrating AI-supported deep learning can be a promising pedagogical strategy for improving mathematical literacy in PGSD programs and may contribute to the development of more adaptive, innovative, and technology-responsive learning environments in higher education.