Big Data education for the masses: MOOCs, modules, & intelligent tutoring systems

描述（由申请人提供）：摘要生物医学科学，高等教育，软件和技术正在同时经历结构性转变。软件和技术发展的惊人步伐正在推动生物医学科学获取大量数据集的能力取得同样惊人的进步。这些新的大生物医学数据集以复杂的测量形式出现，例如大脑，基因组，蛋白质组和人类生物组或大型数据库，例如电子健康记录。大数据问题，如处理、测量和分析技术的可重复性，变得越来越复杂和重要。在所有领域中，研究人员在分析和解释这些新数据集方面存在知识缺口，目前的高等教育模式无法满足对这种培训的贪得无厌的需求。我们建议在两个领域就这些问题取得实质性进展。具体来说，我们建议使用大规模开放式在线课程（MOOC）创建两个系列，一个在神经成像和基因组学。这些系列将允许灵活的，学生节奏，低成本的可扩展培训成千上万的学生。沿着这些系列，我们建议创建模块化的大数据生物统计内容，可供学生和教师使用。这项工作将与一个名为swirl的智能辅导系统的工作并行。这个应用程序建议使用swirl为学生创建丰富的游戏化学习环境。所有的材料创建从这个赠款将是开放和免费的。

DESCRIPTION (provided by applicant): Abstract Biomedical science, higher education, software and technology are simultaneously undergoing tectonic shifts. The amazing pace of software and technological development are driving equally amazing advances in the ability to acquire massive data sets in the biomedical sciences. These new Big Biomedical data sets come in the form of complex measurements, such as that of the brain, genome, proteome and human biome or massive databases, such as with electronic health records. Big Data issues, such as reproducibility of processing, measurement and analysis techniques, are increasingly complex, and crucial. Across all domains there is a knowledge gap of researchers to analyze and interpret these new data sets and the current higher education model cannot meet the insatiable demand for this training. We propose to make substantial progress on these issues in two domains. Specifically, we propose to use Massive Open Online Courses (MOOCs) to create two series, one in neuroimaging and one in genomics. These series will allow for flexible, student paced, low cost scalable training for tens of thousands of students. Along with these series, we propose the creation of modular Big Data biostatistical content that can be used by students as well as teachers. This effort will be parallel to work on an intelligent tutoring syste called swirl. This application proposes to use swirl to create rich, gamified learning environments for students. All of the material created from this grant will be open access and free.