Descriptive Analysis of Artificial Intelligent-Based Physics Learning For Biology: Benefits and Opportunities

This study examines the effectiveness of Artificial Intelligence (AI)-based Physics learning for Biology Students in the FMIPA Unram Environment. Using qualitative research methodology, a survey was conducted on 20 students from the Mathematics and Natural Sciences faculty of the Biology study program, with a focus on patterns and perceptions of the use of AI in physics learning. The aim of this research is to investigate how AI influences physics learning. Data analysis was carried out using Excel to obtain frequency and percentage distributions, which showed that the majority of respondents agreed to AI in physics learning regarding the use of social media. The research results showed that 40% of participants felt that the use of AI in physics learning was not good, while 26.67% felt that the use of AI was good in physics learning. These findings underline the use of AI in physics learning, thus showing. In conclusion, although AI helps biology students in learning physics, they do not always have to depend on AI. This study highlights the importance of using AI wisely.