Agriculture students’ use of generative artificial intelligence for microcontroller programming

Abstract Microcontrollers are widely used in agriculture, yet most undergraduate agriculture students do not have the programming skills necessary to make use of these devices in their academic programs or careers. However, generative artificial intelligence (AI) chatbots, such as ChatGPT, have the ability to write complex microcontroller programs when properly queried. The study was conducted to determine the effects of undergraduate agriculture students’ ( n = 22) use of ChatGPT to write a microcontroller program on their programming task performance, self‐efficacy, and attitudes toward generative AI. Nine of 11 (81.8%) student pairs were successful in the ChatGPT‐assisted programming activity, requiring between one (33.3%) and six (11.1%) queries to develop their programs. The two unsuccessful pairs used either one or two queries and produced somewhat functional programs that did not fully operate as specified. Pre‐ and posttest surveys indicated significant ( p < 0.001) increases in self‐efficacy for writing microcontroller programs, for using ChatGPT to write microcontroller programs, and attitudes toward generative AI. This research confirmed that undergraduate agriculture students can successfully use generative AI chatbots to write microcontroller programs and that successful task completion increases student self‐efficacy. Further research is needed to determine best practices for using generative AI in teaching and learning microcontroller programming.