Comparative Study of ChatGPT’s Prompts for Novice Arduino Maker

This study examines the role of ChatGPT in supporting novice Makers during Arduino project development, with a focus on how the structure and length of user-initiated prompts influence guidance quality. A qualitative comparative analysis was conducted to evaluate two prompting approaches: Long-Form prompts and Short-Form prompts. These approaches were tested across three Arduino projects: LED Blink Adjust, Sensor Display System, and IR RemoteControlled Robot. Key criteria for comparison included instruction accuracy, clarity, completeness, troubleshooting support, and user effort. The findings indicate that Long-Form prompts provide more comprehensive and beginner-friendly guidance, significantly reducing user effort in projects involving external libraries by offering detailed instructions for setup, integration, and troubleshooting. This study underscores the importance of well-structured and detailed user prompts in enhancing the educational potential of AI tools and fostering creativity within the Maker community.