Large Language Models (LLMs), a class of Artificial intelligence (AI) tools, are reshaping programming education, allowing novices to take on tasks that go beyond traditional CS1-style problems. While these tools lower barriers, little is known about the factors that shape students' successful programming or learning in such contexts.

Although hybrid courses have become increasingly common in higher education, it remains uncertain whether a student's experience of a course is consistent between in-person and online modalities. To investigate this, we analyzed student modality and discussion data from the Spring 2023 offering of an elective data science course where students are allowed to attend each lecture in person or synchronously online.