  With recent advances in generative AI, conversational models like ChatGPT
have become feasible candidates for TAs. We investigate the practicality of
using generative AI as TAs in introductory programming education by examining
novice learners' interaction with TAs in a subgoal learning environment. To
compare the learners' interaction and perception of the AI and human TAs, we
conducted a between-subject study with 20 novice programming learners. Learners
solve programming tasks by producing subgoals and subsolutions with the
guidance of a TA. Our study shows that learners can solve tasks faster with
comparable scores with AI TAs. Learners' perception of the AI TA is on par with
that of human TAs in terms of speed and comprehensiveness of the replies and
helpfulness, difficulty, and satisfaction of the conversation. Finally, we
suggest guidelines to better design and utilize generative AI as TAs in
programming education from the result of our chat log analysis.
