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

面向大众的大数据教育：MOOC、模块、

基本信息

批准号：
8829370
负责人：
BRIAN Scott CAFFO
金额：
$ 21.6万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-29 至 2017-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8829370
关键词：
Adopted Amaze Area Attention Automobile Driving Big Data Biological Biology Brain Clinical Trials Communities Complex Computer software Cost Analysis Data Data Analyses Data Collection Data Set Databases Development Dimensions Discipline Drops Education Educational Curriculum Educational Models Educational process of instructing Electronic Health Record Enrollment Environment Generations Genes Genome Genomics Grant Head Human Image Knowledge Laboratories Learning Learning Module Machine Learning Measurement Measures Medical Medicine Modeling Molecular Biology Molecular Medicine Multivariate Analysis Persons Population Principal Investigator Proteome Public Health Public Health Nurses Public Health Nursing Race Research Research Personnel Resolution Science Scientist Series Services Solutions Stream Students System Systems Biology Techniques Technology Testing Time TimeLine Touch sensation Training Training Programs Universities Work abstracting cost density flexibility instructor lectures meetings multidisciplinary neuroimaging new technology novel strategies open source operation process repeatability programs public health relevance research study skills statistics teacher

Adopted Amaze Area Attention Automobile Driving Big Data Biological Biology Brain Clinical Trials Communities Complex Computer software Cost Analysis Data Data Analyses Data Collection Data Set Databases Development Dimensions Discipline Drops Education Educational Curriculum Educational Models Educational process of instructing Electronic Health Record Enrollment Environment Generations Genes Genome Genomics Grant Head Human Image Knowledge Laboratories Learning Learning Module Machine Learning Measurement Measures Medical Medicine Modeling Molecular Biology Molecular Medicine Multivariate Analysis Persons Population Principal Investigator Proteome Public Health Public Health Nurses Public Health Nursing Race Research Research Personnel Resolution Science Scientist Series Services Solutions Stream Students System Systems Biology Techniques Technology Testing Time TimeLine Touch sensation Training Training Programs Universities Work abstracting cost density flexibility instructor lectures meetings multidisciplinary neuroimaging new technology novel strategies open source operation process repeatability programs public health relevance research study skills statistics teacher

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项目摘要

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.

描述（申请人提供）：摘要生物医学科学，高等教育，软件和技术同时进行构造转变。软件和技术发展的惊人速度正在推动在生物医学科学中获得大量数据集的能力的同样惊人的进步。这些新的大型生物医学数据集以复杂测量的形式出现，例如大脑，基因组，蛋白质组和人类生物群落或大型数据库，例如电子健康记录。大数据问题，例如处理，测量和分析技术的可重复性，越来越复杂且至关重要。在所有领域中，研究人员都有一个知识差距来分析和解释这些新数据集，而当前的高等教育模型无法满足对这项培训的无限需求。我们建议在两个领域的这些问题上取得重大进展。具体而言，我们建议使用大型开放在线课程（MOOC）创建两个系列，一个在神经影像学中，另一种是基因组学。这些系列将允许为成千上万的学生提供灵活的，学生节奏，低成本的可扩展培训。与这些系列相同，我们建议创建学生和老师可以使用的模块化大数据生物统计内容。这项工作将平行于使用称为Swirl的智能辅导系统。该应用程序建议使用漩涡为学生创建丰富的游戏学习环境。这笔赠款创建的所有材料将是开放访问权限和免费的。