PENGARUH PEMBELAJARAN DEEP LEARNING TERHADAP DIMENSI PROFIL PELAJAR BERPIKIR KRITIS DALAM MUATAN MATEMATIKA SD MATERI OPERASI HITUNG PEMBAGIAN BERBANTUAN AI - Aulia Usman; Luqman Rohmad Maghribi; Fauzan Nafis Firdaus; Darul Mutakin; Pipit Novita (Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan, 2026)
This study examines the effect of deep learning approaches assisted by Artificial Intelligence (AI) on the critical thinking dimension of graduate profiles in elementary school mathematics, specifically on division operations. Using a quasi-experimental design with pretest-posttest control group, the study involved grade IV students as subjects. Data were collected through critical thinking tests validated through expert judgment and empirical trials. Reliability was tested using Cronbach's Alpha, yielding a coefficient of 0.817 (high category). Inferential analysis employed the Independent Sample T-Test following normality (Shapiro-Wilk) and homogeneity (Levene) tests. Results indicate a significant difference in posttest scores between the experimental group (deep learning with AI) and the control group (conventional). Students in the experimental class demonstrated higher ability to analyze, evaluate, infer, and communicate mathematical reasoning. AI-assisted deep learning positively influenced student engagement, motivation, and eco-digital literacy competence, supporting the formation of the Pancasila Student Profile, particularly critical thinking, independence, and reflective learning. These findings confirm that integrating AI technology in elementary mathematics effectively promotes higher-order thinking skills aligned with 21st-century education demands.