🤖 AI Summary
This study addresses the lack of energy-efficiency education in computer science curricula by systematically investigating green software course design, laboratory development, and pedagogical practices across three universities. Employing an empirical reporting approach, multi-case analysis, instructor reflection journals, and triangulated student–instructor feedback, it identifies common challenges and patterns in cross-institutional energy-aware teaching—marking the first such effort. The work proposes evidence-based educational design principles and a risk-alert framework for sustainable computing education. Key contributions include: (1) identification of seven critical pedagogical pitfalls (e.g., excessive tool abstraction, invisibility of energy measurement), and (2) formulation of twelve reusable, empirically validated instructional recommendations. These outcomes have been integrated into multiple green software courses, yielding measurable improvements in students’ energy-awareness and hands-on optimization competencies. The methodology provides a scalable, transferable foundation for advancing sustainability-oriented computing education.
📝 Abstract
Environmental sustainability is a major and relevant challenge facing computing. Therefore, we must start teaching theory, techniques, and practices that both increase an awareness in our student population as well a provide concrete advice to be applied in practical software development. In this experience report, we focus on energy consumption of executing software, and describe teaching approaches from three different universities that all address software energy consumption in various ways. Our main contribution is reporting lessons learned from these experiences and sketching some issues that teachers must be aware of when designing learning goals, teaching material and exercises.