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

在数据、设施或专业设备的可用性或获取方面存在严重紧迫性的情况下，包括对自然或人为灾害以及类似意外事件（如COVID-19大流行）的快速响应研究，传统黑人学院和大学本科项目（HBCU-UP）支持RAPID项目。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知识的愿望的强大学习措施的影响。它将培养有效、高效和引人入胜的远程学习设计师，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解决方案。本科生作为研究人员参与本项目。该项目的目标是了解如何优化知识内容类型的成功学习，例如数据相关问题解决活动的程序，特别是在强制性远程教育的情况下。COVID-19大流行带来的丰富数据资源提供了独特的条件，适合设计和开发用于学习程序的教育技术干预措施，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”的理论框架为指导，以产生稳健的学生学习。将在从COVID-19大流行的复杂数据资源中获取知识的学习经验设计师群体和冠状病毒基因组学和环境生存的非正式学习者群体中开发和调查两种在线教育技术干预措施。将实施一种“活体”实验方法，结合因果原则和真实的在线教学事件，有或没有生态控制组。学习事件的交易和工件将被分析，以检测预测稳健学习和复杂认知活动表现的特征。教育后干预评估将衡量学术和专业上的成功，包括对学习过程的满意度、有效处理复杂数据集的自信、从事数据职业的愿望，以及参与制定数据驱动的COVID-19大流行解决方案。该RAPID奖由教育和人力资源理事会人力资源开发司黑人历史学院和大学本科项目颁发，资金来自《冠状病毒援助、救济和经济安全（关怀）法案》。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.