Integrating generative AI in data science programming: Group differences in hint requests

Abstract

Generative AI applications have increasingly gained visibility in recent educational literature. Yet less is known about how access to generative tools, such as ChatGPT, influences help-seeking during complex problem-solving. In this paper, we aim to advance the understanding of learners' use of a support strategy (hints) when solving data science programming tasks in an online AI-enabled learning environment. The study compared two conditions: students solving problems in DaTu with AI assistance (N = 45) and those without AI assistance (N = 44). Findings reveal no difference in hint-seeking behavior between the two groups, suggesting that the integration of AI assistance has minimal impact on how individuals seek help. The findings also suggest that the availability of AI assistance does not necessarily reduce learners’ reliance on support strategies (such as hints). The current study advances data science education and research by exploring the influence of AI assistance during complex data science problem-solving. We discuss implications and identify paths for future research.

Keywords

• Hints
• AI-Assistance
• Artificial intelligence
• Feedback
• Help seeking
• Data science programming