  Help-seeking is a critical way for students to learn new concepts, acquire
new skills, and get unstuck when problem-solving in their computing courses.
The recent proliferation of generative AI tools, such as ChatGPT, offers
students a new source of help that is always available on-demand. However, it
is unclear how this new resource compares to existing help-seeking resources
along dimensions of perceived quality, latency, and trustworthiness. In this
paper, we investigate the help-seeking preferences and experiences of computing
students now that generative AI tools are available to them. We collected
survey data (n=47) and conducted interviews (n=8) with computing students. Our
results suggest that although these models are being rapidly adopted, they have
not yet fully eclipsed traditional help resources. The help-seeking resources
that students rely on continue to vary depending on the task and other factors.
Finally, we observed preliminary evidence about how help-seeking with
generative AI is a skill that needs to be developed, with disproportionate
benefits for those who are better able to harness the capabilities of LLMs. We
discuss potential implications for integrating generative AI into computing
classrooms and the future of help-seeking in the era of generative AI.
