Unlocking the Potential of Python-Based Simulations: Understanding the Needs and Expectations of Future Physics Educators
Abstract
Teaching wave phenomena and optics remains challenging due to their abstract and highly visual nature. Pre-service physics teachers often struggle to form accurate mental representations, which hinders conceptual understanding. This study examined the needs, learning challenges, and expectations of future physics educators regarding Python-based simulations for learning optical waves to support conceptual understanding through dynamic visualization, interactive parameter exploration, and multiple representations of wave phenomena. A convergent parallel mixed-methods design was employed, integrating course-task analysis and a needs-assessment form with classroom observations and semi-structured interviews involving 60 third-semester physics education students at a state university in Indonesia. The novelty of this study lies in its integration of students’ conceptual difficulties, technological readiness, and simulation expectations as a foundation for designing Python-based optical wave simulations tailored to physics teacher education. Quantitative findings showed that many students relied on procedural calculation without adequate conceptual explanation and experienced difficulties in interpreting interference and diffraction phenomena. Students strongly preferred dynamic visualizations and stepwise schematic explanations, while many also emphasized the importance of adjustable visual parameters and multiple representations in simulations. Qualitative findings highlighted expectations for slow-motion visualization, comparative parameter exploration, and introductory tutorial support. The study concludes that understanding students’ perspectives is critical to designing effective educational simulations that enhance conceptual understanding and improve learning of abstract optical wave concepts.
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DOI: https://doi.org/10.20527/jmscedu.v6i1.18648
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