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Bridging the Python Training Gap for Bioscientists in Brazil: Improvements and Challenges
Gustavo Schiavone Crestana1, Ubiratan da Silva Batista2, Michelli Inácio Gonçalves Funnicelli3
1Campus Luiz de Queiroz, Department of Genetics, Genomics Group, University of São Paulo (USP), Piracicaba, São Paulo, Brazil.
Summary
Bioscientists need programming skills for big data. The Brazilian Python Workshop for Biological Data adapted its curriculum with new strategies to improve Python training and promote scientific reproducibility.
Area of Science:
- Biological data analysis
- Computational biology education
Background:
- High-throughput technologies generate large biological datasets.
- Bioscientists require advanced data manipulation and analysis skills.
- A gap exists in programming training for bioscientists.
Purpose of the Study:
- Describe advancements in the Brazilian Python Workshop for Biological Data (2021-2022).
- Enhance Python training for bioscientists in Brazil.
- Provide recommendations for similar educational initiatives.
Main Methods:
- Implemented structural and coordinative innovations (committees, code of conduct).
- Updated feedback forms for real-time adjustments and expanded event reach.
- Introduced new didactic strategies (pair-teaching, code clubs, ICT integration).
- Emphasized programming best practices and scientific reproducibility (PEP8).
- Intensified scientific dissemination (social media, international events).
Main Results:
- Workshop structure and coordination were improved.
- Didactic strategies enhanced learning outcomes.
- Focus on best practices and reproducibility increased.
- Event reach and geographical diversity expanded.
- Scientific dissemination efforts were intensified.
Conclusions:
- Continuous adaptation is crucial for effective bioscience programming workshops.
- New strategies improved learning and engagement.
- The workshop successfully addressed the need for Python training in Brazil.
- Recommendations are provided for future initiatives and educators.
