Exploring the Community of Inquiry in Online Computing Education: Student Perceptions and Opportunities for Generative AI
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.
Thu 16 AprDisplayed time zone: Brasilia, Distrito Federal, Brazil change
11:00 - 12:30 | Education 4Software Engineering Education and Training (SEET) at Oceania VI Chair(s): Andreia Malucelli Pontifícia Universidade Católica do Paraná | ||
11:00 15mTalk | Exploring the Community of Inquiry in Online Computing Education: Student Perceptions and Opportunities for Generative AI Software Engineering Education and Training (SEET) | ||
11:15 15mTalk | Prompting Without Principles: Are Students Transferring Software Engineering Knowledge to LLM Use? Software Engineering Education and Training (SEET) Leonardo Da Silva Sousa Carnegie Mellon University, USA, Ipek Ozkaya Carnegie Mellon University, James Ivers Carnegie Mellon University, Celina Cywinska Carnegie Mellon University, Bingyu Xie Carnegie Mellon University, Mena Kostial Carnegie Mellon University Software Engineering Institute, Tapajit Dey Carnegie Mellon University Software Engineering Institute, Robert Edman Carnegie Mellon Software Engineering Institute | ||
11:30 15mTalk | "Can you feel the vibes?": An exploration of novice programmer engagement with vibe coding Software Engineering Education and Training (SEET) Kiev Gama Universidade Federal de Pernambuco, Filipe Calegario Universidade Federal de Pernambuco, Victoria Jackson University of Southampton, Alexander Nolte Eindhoven University of Technology, Luiz Morais Universidade Federal de Pernambuco, Vinicius Cardoso Garcia Universidade Federal de Pernambuco | ||
11:45 15mTalk | The Clash of Codes: From Peer-to-Peer Duplication to AI-Generation in Introductory Programming Assignments Software Engineering Education and Training (SEET) Jose Maria Zuzarte Reis Claver Vrije Universiteit Amsterdam, i Mahbod Tajdin Vrije Universiteit Amsterdam, Mauricio Verano Merino Vrije Universiteit Amsterdam Pre-print | ||
12:00 15mTalk | AI-Assisted Code Review as a Scaffold for Code Quality and Self-Regulated Learning: An Experience Report Software Engineering Education and Training (SEET) Eduardo Araujo Oliveira The University of Melbourne, Michael Fu The University of Melbourne, Patanamon Thongtanunam University of Melbourne, Sonsoles López-Pernas University of Eastern Finland, Mohammed Saqr University of Eastern Finland | ||
12:15 15mTalk | Amplifiers or Equalizers? A Longitudinal Study of LLM Evolution in Software Engineering Project-Based Learning Software Engineering Education and Training (SEET) | ||