RAPID: Educational Interventions for Undergraduate Students and Informal Learners for Robust Learning of COVID-19 Knowledge

历史上的黑人学院和大学-本科生计划（HBCU-UP）支持RAPID项目，当有严重的紧迫性，或获得，数据，设施或专用设备，包括对自然或人为灾害和类似的意外事件的快速反应研究，如COVID-19大流行病。 白求恩库克曼大学的项目旨在调查两种教育干预措施对长期保留或未来学习COVID-19知识的愿望的稳健学习措施的影响。 它将产生有效，高效和参与远程学习的设计师，同时为本科生和非正式学习者提供相关技能和能力，为当前的COVID-19和未来的疾病爆发提供跨学科的解决方案。本研究以大学生为研究对象，旨在探讨如何在远程教育的强制性条件下，优化学生对数据相关问题解决活动等知识内容类型的成功学习。COVID-19疫情带来的丰富数据资源为设计和开发教育技术干预措施提供了独特的条件，以解决数据流、数据管理和数据分析领域的数据挑战。本研究以知识-学习-教学理论框架为指导，以促进学生的学习。将开发两种在线教育技术干预措施，并在学习经验设计者群体中进行调查，以从COVID-19大流行的复杂数据资源中生成知识，以及在冠状病毒基因组学和环境生存的非正式学习者中进行调查。一个“在体内”的实验方法将被实施，结合因果关系的原则和真实的在线教学活动，或没有一个生态控制组。将分析学习事件的事务和工件，以检测预测鲁棒学习和复杂认知活动性能的特征。 教育后干预评估将获取学术和专业成功的衡量标准，包括对学习过程的满意度，有效处理复杂数据集的自信心，追求数据职业的愿望，以及参与开发COVID-19大流行的数据驱动解决方案。这个快速奖是由历史上的黑人学院和大学-人力资源开发部本科课程，教育和人力资源局，使用冠状病毒援助，救济和经济安全（CARES）法案的资金。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

The Historically Black Colleges and Universities - Undergraduate Program (HBCU-UP) supports RAPID projects when there is a severe urgency with regard to availability of, or access to, data, facilities or specialized equipment, including quick-response research on natural or anthropogenic disasters and similar unanticipated events, such as the COVID-19 pandemic. The project at Bethune Cookman University seeks to investigate the effects of two educational interventions on the robust learning measures of long-term retention or desire for future learning of COVID-19 knowledge. It will produce designers of effective, efficient, and engaging distance learning while equipping undergraduate students and informal learners with relevant skills and competencies to contribute transdisciplinary solutions to the current COVID-19 and future disease outbreaks. Undergraduate students are involved as researchers in this project.The goal of the project is to understand how to optimize the successful learning of knowledge content types such as procedures for data associated problem solving activities, especially in the circumstances of mandatory remote education. The abundance of data resources resulting from the COVID-19 pandemic presents unique conditions suitable to design and develop educational technology interventions for learning procedures to solve data challenges in areas of data flow, data curation, and data analytics. The research is guided by the Knowledge-Learning-Instruction theoretical framework for producing robust student learning. Two online educational technology interventions will be developed and investigated among cohorts of designers of learning experiences on generating knowledge from complex data resources on COVID-19 pandemic, and among informal learners of the genomics and environmental survival of coronaviruses. An “in vivo” experimentation approach will be implemented that combines causal principles and real online instructional events with or without an ecological control group. The transactions and artifacts of learning events will be analyzed to detect features that predict robust learning and the performance of complex cognitive activities. Post-educational intervention assessments will capture academic and professional success measures including satisfaction with the learning process, self-confidence to work effectively with complex datasets, desire to pursue data careers, and involvement in developing data-driven solutions to COVID-19 pandemic. This RAPID award is made by the Historically Black Colleges and Universities - Undergraduate Program in the Division of Human Resource Development, Directorate of Education and Human Resources, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.