Data_Sheet_1_Interdisciplinary and Transferable Concepts in Bioinformatics Education: Observations and Approaches From a UK MSc Course.pdf

Bioinformatics is a highly interdisciplinary subject, with substantial and growing influence in health, environmental science and society, and is utilised by scientists from many diverse academic backgrounds. Education in bioinformatics therefore necessitates effective development of skills in interdisciplinary collaboration, communication, ethics, and critical analysis of research, in addition to practical and technical skills. Insights from bioinformatics training can additionally inform developing education in the tightly aligned and emerging disciplines of data science and artificial intelligence. Here, we describe the design, implementation, and review of a module in a UK MSc-level bioinformatics programme attempting to address these goals for diverse student cohorts. Reflecting the philosophy of the field and programme, the module content was designed either as “diversity-addressing”—working toward a common foundation of knowledge—or “diversity-exploiting”—where different student viewpoints and skills were harnessed to facilitate student research projects “greater than the sum of their parts.” For a universal introduction to technical concepts, we combined a mixed lecture/immediate computational practical approach, facilitated by virtual machines, creating an efficient technical learning environment praised in student feedback for building confidence among cohorts with diverse backgrounds. Interdisciplinary group research projects where diverse students worked on real research questions were supervised in tandem with interactive contact time covering transferable skills in collaboration and communication in diverse teams, research presentation, and ethics. Multi-faceted feedback and assessment provided a constructive alignment with real peer-reviewed bioinformatics research. We believe that the inclusion of these transferable, interdisciplinary, and critical concepts in a bioinformatics course can help produce rounded, experienced graduates, ready for the real world and with many future options in science and society. In addition, we hope to provide some ideas and resources to facilitate such inclusion.

生物信息学是一门高度跨学科的学科，其在健康、环境科学和社会领域的深远影响日益增强，并受到来自众多不同学术背景的科学家们的广泛应用。因此，生物信息学的教育要求在跨学科合作、沟通、伦理以及研究批判性分析等技能的有效培养之外，还需注重实践和技术技能的提升。此外，生物信息学培训的洞见还能够为数据科学和人工智能等紧密相关且新兴学科的不断发展提供指导。在本研究中，我们详细描述了一项英国硕士学位生物信息学课程模块的设计、实施和评估过程，旨在满足不同学生群体的这些目标。该模块内容的设计理念既包括“多样性应对”——致力于构建共同的知识基础，也包括“多样性利用”——充分利用不同学生的观点和技能，以促进学生的研究项目实现“大于其各部分之和”的效果。为了提供通用的技术概念入门，我们结合了混合式讲座与即时计算实践的方法，通过虚拟机辅助，创造了一个高效的技术学习环境，这一环境得到了学生反馈的高度赞扬，因为它能够增强不同背景学生群体的自信心。跨学科团队研究项目，其中不同背景的学生共同解决真实的研究问题，在互动接触时间中得到监督，涵盖了跨团队协作与沟通的可迁移技能、研究展示和伦理等方面。多方面的反馈和评估与真实同行评审的生物信息学研究保持了建设性的对接。我们坚信，将这些可迁移的、跨学科的以及批判性的概念纳入生物信息学课程中，有助于培养出全面、经验丰富的毕业生，使他们为现实世界做好准备，并在科学和社会领域拥有众多的未来选择。此外，我们还希望提供一些想法和资源，以促进此类内容的融入。