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Moving a Flipped Class Online To Teach Python to Biomedical Ph.D. Students during COVID-19 and Beyond
Nathalie A Vladis1, Bradley I Coleman2
1Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.
Journal of Microbiology & Biology Education
|October 1, 2021
Summary
Biomedical Ph.D. students gained confidence in Python for research using a flexible, flipped learning approach. This method, adaptable to online or in-person formats, enhances computational training and peer collaboration.
Area of Science:
- Biomedical Sciences
- Computational Biology
- Graduate Education
Background:
- The increasing prevalence of big data in biomedical research necessitates advanced computational skills for Ph.D. students.
- Traditional graduate curricula face challenges integrating essential quantitative and computational training due to time, faculty, and scalability constraints.
Purpose of the Study:
- To evaluate a flipped learning model for teaching Python programming to biomedical Ph.D. students.
- To assess the effectiveness of this model in both in-person and fully remote (Zoom-based) formats.
Main Methods:
- A flipped classroom approach combining a pre-existing online Python course with group problem-solving sessions.
- Adaptation of the in-person sessions to small-group Zoom meetings during COVID-19 pandemic-related shutdowns.
Main Results:
- Students demonstrated increased confidence in utilizing Python for their thesis research across both in-person and remote formats.
- The remote format fostered greater peer-to-peer learning and support due to increased student reliance on classmates.
Conclusions:
- The flexible, scalable flipped learning model effectively enhances computational training for biomedical Ph.D. students.
- This approach successfully addresses the growing need for Python proficiency in biomedical research and can be adapted to various delivery modes.
