AI support for data scientists: An empirical study on workflow and alternative code recommendations.

ABSTRACT: Despite the popularity of AI assistants for coding activities, there is limited empirical work on whether these coding assistants can help users complete data science tasks. Moreover, in data science programming, exploring alternative paths has been widely advocated, as such paths may lead to diverse understandings and conclusions (Gelman and Loken 2013; Kale et al. 2019). Whether existing AI-based coding assistants can support data scientists in exploring the relevant alternative paths remains unexplored. To fill this gap, we conducted a mixed-methods study to understand how data scientists solved different data science tasks with the help of an AI-based coding assistant that provides explicit alternatives as recommendations throughout the data science workflow. Specifically, we quantitat

SUBMITTER: Ramasamy D 

PROVIDER: S-EPMC12227384 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature