IEEE Access (Jan 2023)
Using PBL and Agile to Teach Artificial Intelligence to Undergraduate Computing Students
Abstract
Project-based learning (PBL) is an active learning methodology focused on developing both soft and hard skills by solving real-world problems. In PBL, teachers act as facilitators while students take charge of their own learning. While the practice of this methodology in computing education has been growing in recent years, it still poses some challenges that need to be addressed. Integrating Scrum and Agile methodologies into PBL can be a valuable addition when teaching computing subjects to students. Therefore, this paper presents a case study of a successful implementation of PBL with Scrum, applying Agile values and principles to teach Artificial Intelligence to undergraduate students. This study contributes to the limited research on Scrum in education, as well as helps bridge the research gap in AI teaching and learning. The case study involved 30 students from an undergraduate computing program, divided into five groups, who successfully developed five different Machine Learning (ML) models to tackle the challenging real-life problem of breast cancer prediction for the Cancer Institute of the State of São Paulo. The findings of the study indicate that the students effectively utilized Scrum and Agile methodologies throughout the process and expressed satisfaction with the approach. Additionally, they developed problem-solving abilities, critical thinking and communication skills, teamwork capabilities, and gained experience in working with real-life situations and problems. The study also demonstrates that the proposed technique aligns with the foundations of the PBL approach in computing education discussed in previous literature. It serves as a valuable resource for future research on PBL implementation, by comparing similarities and differences with existing literature and discussing the strategies employed to address implementation challenges.
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