Related Experiment Video
Updated: Aug 5, 2026
10:17
Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience
Published on: November 15, 2024
Breaking Barriers in Large Classes: Using Cloud Computing and Computational Biology to Implement Research-Inspired
Christopher E Berndsen1, Kathryn E Shenk2, Alyssa Young2
1Department of Chemistry and Biochemistry, James Madison University, Harrisonburg, Virginia, USA.
Summary
Large biochemistry courses can now offer research experiences through a cloud-based project. This approach enhances student confidence in analyzing protein structures and functions, overcoming access barriers.
Area of Science:
- Biochemistry Education
- Computational Biology
- Undergraduate Research
Background:
- Course-based undergraduate research experiences (CUREs) are valuable but difficult to implement in large lectures.
- Large lecture courses face challenges with class size and content demands, limiting research integration.
Purpose of the Study:
- To develop and evaluate a research-inspired project for a large-enrollment (70+ students) Biochemistry lecture course.
- To complement existing curriculum with novel research project experience.
- To address access barriers using cloud-based computational tools.
Main Methods:
- Implemented a semester-long, four-module project focused on protein structure and function.
- Utilized cloud-based computational techniques, specifically Google Colaboratory (Colab), for software accessibility.
- Incorporated information literacy and data management training with a science librarian.
- Culminated in an individual project analyzing novel protein variants.
Main Results:
- Over 250 students participated since Fall 2024.
- Student self-assessments indicated increased confidence in analyzing molecular structures.
- Students reported improved ability to connect genetic mutations to protein function.
- Enhanced skills in utilizing scientific databases such as UniProt were observed.
Conclusions:
- Research-inspired curricula can be successfully integrated into large, content-heavy lecture courses.
- Accessible cloud-computing resources, like Colab, effectively overcome implementation barriers.
- This model enhances student learning in biochemistry and research methodologies.
