GenAI Reliance in Physics Learning: Its Relationship with Physics Anxiety and Students’ Physics Learning Outcomes
DOI:
https://doi.org/10.33394/j-ps.v14i4.22775Keywords:
GenAI, Gen AI reliance, Physics anxiety, Physics learning outcomesAbstract
The increasing use of Generative Artificial Intelligence (GenAI) in education has raised questions about its relationship with students’ learning experiences and academic outcomes. This study aimed to examine the relationships among students’ GenAI reliance, physics anxiety, and physics learning outcomes. A quantitative correlational design was employed involving 100 tenth-grade students from one senior high school in Lamongan, Indonesia, recruited through convenience sampling. Data were collected using questionnaires measuring GenAI reliance and physics anxiety, while students’ physics learning outcomes were obtained from teacher records. The data were analyzed using descriptive statistics and Spearman’s rank-order correlation. The findings indicated a positive correlation between GenAI reliance and physics anxiety (ρ = 0.456, p < 0.001), as well as a positive correlation between GenAI reliance and physics learning outcomes (ρ = 0.347, p < 0.001). Meanwhile, the relationship between physics anxiety and physics learning outcomes was positive but not statistically significant (ρ = 0.171, p = 0.089). Responses to the open-ended questions suggested that students used GenAI primarily to understand physics concepts, obtain explanations, and identify steps for solving problems. Some students also reported using GenAI because they lacked confidence in their own answers or feared making mistakes. These findings indicate that GenAI reliance is associated with physics anxiety and students’ physics learning outcomes. However, the correlational design of this study does not establish causal relationships, and students’ learning outcomes may also be associated with other factors beyond their reliance on GenAI.
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Copyright (c) 2026 Tasya Febriana Feodika, Habibi Habibi, Ririn Yuniawan, Mokhammad Yusuf, Faridatul Amiroh, Jelita Puspita Ningrum Khoirunnisa
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