Breaking Barriers in Large Classes: Using Cloud Computing and Computational Biology to Implement Research‐Inspired Curricula in Biochemistry I

Course-based undergraduate research experiences (CUREs) are a high impact instructional approach but are challenging to implement in large lecture courses due to class size and content demands. We describe the evolution of a research-inspired project in a large-enrollment (70+ students) Biochemistry lecture course. Our goal was to integrate a project that complements the rigid content while providing experience working on a novel research project. We addressed access barriers by expanding the use of cloud-based computational techniques, notably Google Colaboratory (Colab), to ensure software accessibility across diverse student devices. The semester-long project is divided into four modules focusing on protein structure and function, culminating in an individual project that studies a novel protein variant and its effects on structure and function. These projects are further supported by a science and math librarian to teach information literacy and data management skills. Since Fall 2024, over 250 students have participated. Student self-assessments demonstrate gains in confidence, particularly in analyzing molecular structures, connecting genetic mutations to protein function, and using scientific databases like UniProt. This model shows that research-inspired curricula can be successfully integrated into large, content-heavy lecture courses by leveraging accessible cloud-computing resources.