Integrated Active Learning Framework for Biomedical BD2K

拟议的项目将为学生和教育工作者创建积极和自适应的开放式在线资源。我们建议为生物医学大数据（BBD）开发两个大规模开放式在线课程（MOOC）。生物信息学家的BBD将针对生物信息学学生，他们知道一些入门编程并需要专注于BBD分析的专业教程。生物学家的BBD将为以前没有接触过编程的生物学家提供有效应用BBD中现有软件工具所需的技能。这些MOOC将有三种不同的自适应学习轨道，有助于根据读者的计算经验指导他们完成课程。如果没有我们在2013年秋季在Coursera上提供第一个生物信息学MOOC（生物信息学算法）的丰富经验，创建这样一个自适应环境是不可能的。通过使我们的学习材料开放供个人学习者和教授使用，我们希望降低阻碍BBD课程在个别大学发展的资源障碍。我们还将在我们的在线Rosalind平台上开发两个新的问题轨道，通过自动测试的挑战促进生物信息学的独立学习。其中一个问题集将集中于实现BBD分析所需的算法;第二个问题集将集中于应用现有的在线工具来分析BBD。通过创建一套全面的评估，我们将消除BBD教授再次考虑自动化自己的家庭作业的需要。结合我们的开放，适应性学习环境的努力，这些问题集将有助于减少在大学创建新的BBD课程的障碍。我们将通过成立BBD教育联盟，培养BBD教育工作者的开放社区。该网络将于2015年在UCSD的RECOMB生物信息学教育会议上成立，该会议将专注于BBD教育。联盟成员将创建开放式学习模块，以补充我们的内容，并向联盟的其他成员提供关于其模块的反馈。这些教育工作者还将在他们自己的大学设计BBD课程。最后，

DESCRIPTION: The proposed project will create active and adaptive open online resources for students and educators. We propose the development of two massive open online courses (MOOCs) for Biomedical Big Data (BBD). BBD for Bioinformaticians will be aimed at bioinformatics students who know some introductory programming and need specialized tutorials focusing on BBD analysis. BBD for Biologists will provide biologists having no previous exposure to programming with the skills required to effectively apply existing software tools in BBD. These MOOCs will have three different adaptive learning tracks that will help guide readers through the courses based on their computational experience. Creating such an adaptive environment would not be possible without our substantial experience in offering the first bioinformatics MOOC, Bioinformatics Algorithms, in fall 2013 on Coursera. By making our learning materials open for use by individual learners and professors, we hope to bring down resource barriers that have prevented BBD courses from growing at individual universities. We will also develop two new problem tracks on our online Rosalind platform that facilitates independent learning of bioinformatics through automatically tested challenges. One of these problem sets will focus on implementing the algorithms required for BBD analysis; the second problem set will focus on applying existing online tools to analyze BBD. By creating a comprehensive set of assessments, we will eliminate the need for BBD professors to ever again think about automating their own homework assignments. Combined with the efforts of our open, adaptive learning environment, these problem sets will help reduce the barriers to creation of new BBD courses at universities. We will foster an open community of BBD educators by forming the BBD Education Alliance. This network will be founded at the RECOMB Conference on Bioinformatics Education at UCSD in 2015, which will focus on BBD education. Members in the alliance will create open learning modules to supplement our content as well as provide feedback to other members of the alliance on their modules. These educators will also work to design BBD courses at their own universities. Finally,