Online learning increasingly offers flexibility and accessibility to students in computing education. However, it also presents drawbacks such as reduced engagement, lack of real-time support, and limited personal interaction. These challenges are particularly consequential in software engineering education, where collaboration, communication, and teamwork are central to both educational and professional practice. Recent advancements in generative artificial intelligence (GenAI) have the potential to revolutionize online learning experiences, necessitating research to understand students’ perceptions of online computing courses and how GenAI could support them. Grounded in the Community of Inquiry (CoI) framework, we explore how GenAI could support online learning experiences. We distributed an online survey, receiving responses from 86 students with experience taking a variety of online computing courses. Our results show that students perceive traditional online courses as lacking support for CoI elements and factors, and they believe GenAI can enhance the learning experience through personalized and timely feedback, task decomposition, reduced social pressure, and responsive, nonjudgmental instructional support. Yet, concerns persist, including AI-generated misinformation and hallucinations in the responses, and the challenge of building social connections and group cohesion with GenAI’s interaction style. Based on our findings, we provide implications and future research directions for leveraging AI to enhance students’ experiences in online learning environments to support effective computing education.

@inproceedings{paperbot12063,
  title = {Exploring the Community of Inquiry in Online Computing Education: Student Perceptions and Opportunities for Generative AI},
  author = {Tianjia Wang and Chris Brown},
  booktitle = {ICSE},
  year = {2026},
  doi = {10.1145/3786580.3786986}
}