*Result*: Lowering Barriers to Coding: Incorporating Generative Artificial Intelligence to Support Data Analysis in a Biology Class.
*Further Information*
*Integrating generative artificial intelligence (AI) into undergraduate biological data analysis education offers a promising approach to lowering barriers to coding for biology majors. As "big data" becomes increasingly relevant in life sciences, essential programming skills often lead to student frustration due to a lack of prior coding experience. To mitigate barriers to coding, ChatGPT, an AI chatbot, was utilized as a debugging assistant in an undergraduate biological data analysis course. This course involves extensive Python programming, data cleaning, and statistical modeling. ChatGPT provided real-time feedback on coding errors, enhancing student engagement and learning efficiency. Informal feedback suggested that AI integration supported more independent troubleshooting and transformed students' approach to coding by making it more accessible. The implementation highlights the potential of AI-assisted tools in education, suggesting they can improve learning outcomes by reducing cognitive barriers associated with programming. [ABSTRACT FROM AUTHOR]*