SOLSTICE project
收藏资源简介：
The SOLution-oriented, STudent-Initiated, Computationally-Enriched (SOLSTICE) <a href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1855886&HistoricalAwards=false">NSF Award Details</a> approach is a teaching method for improving graduate student training in data-intensive fields. The approach seeks to enhance students' knowledge, skills, and attitudes in data sciences to solve complex problems, think critically, and effectively communicate across inter-generational, trans-disciplinary research teams. Using a data-intensive, project-based learning approach, graduate students work collaboratively to design, evaluate, and disseminate research in team environments. As data scientists, these students will learn how to pose research questions, translate information into potential actions, develop data collection, analysis, and visualization schemes and protocols, and exchange information, data methods, and results tailored to various audiences. Educational resources developed during this study will then be available to guide future faculty development and training processes. Read more here: <a href="https://sites.tufts.edu/naumovalabs/solstice-info/">Visit Naumova Labs' SOLSTICE Information Page</a>
面向解决方案、学生主导、计算赋能（SOLution-oriented, STudent-Initiated, Computationally-Enriched，缩写SOLSTICE）的教学方案，相关资助详情可参见<a href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1855886&HistoricalAwards=false">美国国家科学基金会（National Science Foundation）资助项目详情</a>。该方案是面向数据密集型领域的研究生培养教学方法，旨在提升学生在数据科学领域的知识储备、专业技能与专业态度，使其能够解决复杂问题、开展批判性思考，并在跨代际、跨学科的研究团队中实现高效沟通协作。依托数据密集型项目式学习模式，研究生将以团队形式开展协作，完成研究的设计、评估与传播工作。作为未来的数据科学从业者，这些学生将学会如何提出研究问题、将信息转化为可行行动方案、制定数据采集、分析与可视化的流程规范，并针对不同受众精准传递信息、数据方法与研究成果。本研究期间开发的教育资源，后续将为未来的教师发展与培训工作提供指导。更多详情可参见：<a href="https://sites.tufts.edu/naumovalabs/solstice-info/">访问瑙莫娃实验室SOLSTICE信息页面</a>
