Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada.
ECOSCOPE, University of British Columbia, Vancouver, British Columbia, Canada.
PLoS Comput Biol. 2021 Feb 25;17(2):e1008661. doi: 10.1371/journal.pcbi.1008661. eCollection 2021 Feb.
We live in an increasingly data-driven world, where high-throughput sequencing and mass spectrometry platforms are transforming biology into an information science. This has shifted major challenges in biological research from data generation and processing to interpretation and knowledge translation. However, postsecondary training in bioinformatics, or more generally data science for life scientists, lags behind current demand. In particular, development of accessible, undergraduate data science curricula has the potential to improve research and learning outcomes as well as better prepare students in the life sciences to thrive in public and private sector careers. Here, we describe the Experiential Data science for Undergraduate Cross-Disciplinary Education (EDUCE) initiative, which aims to progressively build data science competency across several years of integrated practice. Through EDUCE, students complete data science modules integrated into required and elective courses augmented with coordinated cocurricular activities. The EDUCE initiative draws on a community of practice consisting of teaching assistants (TAs), postdocs, instructors, and research faculty from multiple disciplines to overcome several reported barriers to data science for life scientists, including instructor capacity, student prior knowledge, and relevance to discipline-specific problems. Preliminary survey results indicate that even a single module improves student self-reported interest and/or experience in bioinformatics and computer science. Thus, EDUCE provides a flexible and extensible active learning framework for integration of data science curriculum into undergraduate courses and programs across the life sciences.
我们生活在一个日益数据驱动的世界中，高通量测序和质谱平台正在将生物学转变为信息科学。这将生物学研究中的主要挑战从数据生成和处理转移到了解释和知识转化。然而，生物信息学的高等教育培训，或者更普遍地说，生命科学家的数据科学培训，落后于当前的需求。特别是，开发易于使用的本科数据科学课程有可能改善研究和学习成果，并使生命科学专业的学生更好地为在公共和私营部门的职业生涯做好准备。在这里，我们描述了体验式本科跨学科教育数据科学（EDUCE）计划，该计划旨在通过多年的综合实践逐步建立数据科学能力。通过 EDUCE，学生完成数据科学模块，这些模块整合到必修和选修课程中，并辅以协调的课外课程活动。EDUCE 计划借鉴了一个实践社区，其中包括来自多个学科的教学助理 (TA)、博士后、教师和研究人员，以克服生命科学家数据科学的几个报告障碍，包括教师能力、学生先前的知识以及与特定学科问题的相关性。初步调查结果表明，即使是一个单一的模块也能提高学生自我报告的在生物信息学和计算机科学方面的兴趣和/或经验。因此，EDUCE 为将数据科学课程整合到生命科学的本科课程和项目中提供了一个灵活且可扩展的主动学习框架。
