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A researcher and graduate student discuss a sparse scatterplot, analysis workflow cards, and handwritten questions about a model choice.
期刊論文2025
期刊論文 152

Stating the data-science step increased acceptance of AI code suggestions, while alternatives alone did not

Dhivyabharathi Ramasamy, Cristina Sarasua, Abraham Bernstein

Empirical Software Engineering

An experiment with 28 data scientists tested a notebook assistant that could include workflow context and offer alternative code recommendations. Naming the data-science step increased acceptance of suggestions, while alternatives alone showed no significant effect. Predictive tasks were easier for the assistant-supported workflow than descriptive analysis. The small study informs interface design; accepting more generated code does not by itself demonstrate better scientific reasoning, reliable findings or improved learner competence.

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AIEDHKAI in Education Hub of Knowledge

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