QUANTUM STORYTELLING ARTIFICIAL INTELLIGENCE (AI) BASED PHYSICS LEARNING TO ENHANCE STUDENTS' CONCEPTUAL INTUITION ON NON-CLASSICAL PHENOMENA

Zohri Ratna (Program Studi PGMI, STIT Palapa Nusantara Lombok NTB, Indonesia)

Jurnal Inovasi Fisika dan Edukasi
Vol. 1 No. 2 (2025): December

Quantum storytelling artificial intelligence–based physics learning is an important aspect of physics education because conventional instructional approaches often fail to support students in developing strong conceptual intuition toward non-classical phenomena that are abstract, probabilistic, and counterintuitive, such as superposition, entanglement, and the quantum uncertainty principle. This limitation highlights the need for further research focusing on innovative instructional strategies that integrate artificial intelligence–driven narrative approaches to bridge students’ conceptual understanding of quantum phenomena. This study aims to examine the effectiveness of quantum storytelling–based physics learning supported by artificial intelligence in enhancing students’ conceptual intuition of non-classical phenomena. The research employed an experimental method with a quasi-experimental design involving an experimental group and a control group. Data were collected through quantum conceptual intuition tests, learning engagement observation sheets, and instructional documentation. The collected data were analyzed using descriptive statistics and inferential analysis through an independent samples t-test. The results indicate that students in the experimental group achieved significantly higher conceptual intuition scores (M = 83.7; SD = 6.4) than those in the control group (M = 70.9; SD = 7.6), with a statistically significant difference (t(58) = 5.61, p < 0.001) and a strong effect size (Cohen’s d = 0.86). These findings demonstrate that the integration of quantum storytelling supported by artificial intelligence effectively strengthens students’ conceptual intuition through narrative, visual, and reflective representations aligned with quantum physics principles. This study provides a significant contribution to the advancement of physics education at both national and international levels by proposing an innovative artificial intelligence–based narrative learning model for non-classical physics instruction. Furthermore, the findings are expected to serve as a reference for future research in quantum physics education, artificial intelligence–supported science learning, and studies on conceptual intuition in abstract physics domains.