Document Type
Conference Proceeding
Abstract
Generative AI, like ChatGPT, is revolutionizing education. While its benefits in personalizing learning and providing formative feedback are well-documented, its full potential remains largely unexplored. This paper focuses on Gemini, Google's AI engine, and investigates its capabilities in a research setting. A doctoral student conducted informal research by applying Gemini to various statistical analyses within a research course. Findings highlight Gemini's strengths and limitations in handling complex statistical tasks. This research contributes to a growing body of research on effectively integrating generative AI tools in academic and research environments.
Recommended Citation
Hannah, Lorin and Chernobilsky, Ellina, "Generative AI and Statistical Analysis: An Exploratory Study" (2024). NERA Conference Proceedings 2024. 12.
https://digitalcommons.lib.uconn.edu/nera-2024/12
