Physic Education

Physics education research is actively exploring innovative methods to enhance student learning and understanding, particularly focusing on integrating data science skills and leveraging artificial intelligence. Current research investigates the use of AI-powered tools like large language models (LLMs) and neural networks (including UNets and CNNs) to provide personalized assistance, automate tasks, and analyze complex datasets within physics curricula. These advancements aim to improve teaching effectiveness, address challenges in data analysis within physics, and ultimately prepare students for a data-driven scientific landscape. The impact of these technologies on student learning and the development of effective pedagogical strategies are key areas of ongoing investigation.