BIGDATA: Collaborative Research: F: Study of a Cyber-Enabled Social Computing Framework for Improving Practice in Online Computing Communities

数据科学技术已经给许多学术领域带来了革命性的变化，并在商业领域带来了巨大的收益。到目前为止，它们在解决美国教育系统中的关键问题方面一直没有得到充分利用，特别是在了解科学、技术、工程和数学(STEM)学习和学习环境、扩大STEM的参与以及增加传统上STEM服务不足的学生的留住方面。教育和人力资源局通过推进大数据科学与工程(BigData)计划的关键技术和技术(BigData)计划的目标是促进对该领域关键问题的基本理解，并促进数据科学在教育研究中的应用。计算已经成为现代科学、技术、工程和数学(STEM)领域实践中不可或缺的一部分。因此，STEM+计算伙伴关系(STEM+C)计划寻求在STEM教学和学习中整合计算方法的使用，并了解这种整合如何提高STEM的学习、参与度和持久性。在这项提案中，首席调查员(PI)将研究许多人独立参与学习计算、在线社区和大规模在线公开课(MOOC)的环境。当人们来到这些环境时，这项活动可能非常有吸引力，因为他们有学习材料的个人目标。然而，在这些环境中的一个挑战是，对学习的支持很少。此外，这些环境不适应学习者的需求。这个项目将解决这两个挑战。PI将首先描述学习者群体的特征，以了解他们的需求，然后根据这些需求设计个性化环境的方法。PI通过提供一个组合的学习工作社区来满足对学习和独立在线工作社区的需求。许多真正的制作社区，如GitHub，并不为想要学习贡献的新手提供支持。同样，许多学习社区，如MOOC和其他在线学习环境，并不为学习者的产品变得真实提供渠道。PIS将结合MOOC和在线社区的数据，发现行为相似的参与者群体，并调查如何支持这些群体的需求。这将导致拟议的新的学习和工作相结合的社区，既提供支持，也为特定课程以外的工作产品提供真正的渠道。

Data science techniques have revolutionized many academic fields and led to terrific gains in the commercial sector. They have to date been underutilized in solving critical problems in the US educational system, particularly in understanding Science, Technology, Engineering and Mathematics (STEM) learning and learning environments, broadening participation in STEM, and increasing retention for students traditionally underserved in STEM. The goals of the Directorate for Education and Human Resources through the Critical Techniques and Technologies for Advancing Foundations and Applications of Big Data Science & Engineering (BIGDATA) program are to advance fundamental understanding of key questions in the field, and catalyze the use of data science in Education Research. Computing has become an integral part of the practice of in modern science, technology engineering, and mathematics (STEM) fields. As a result, the STEM+Computing Partnership (STEM+C) program seeks to integrate the use of computational approaches in STEM teaching and learning and understand how this integration can improve STEM learning, engagement, and persistence. In this proposal, the Principal Investigators (PIs) will examine environments that many people engage in independently to learn computing, online communities and massive open online courses (MOOCs). This activity could be very compelling as people come to these environments because they have personal goals to learn the material. However, a challenge in these environments is that there is little support for learning. In addition, these environments are not adaptive to learners' needs. This project will tackle both of these challenges. The PIs will first characterize groups of learners to understand their needs and then design approaches to personalizing the environments based on those needs.The PIs address a need for both learning and independent online work communities by providing a combined learning work community. Many authentic production communitites, such as GitHub, do not provide support for novices who want to learn to contribute. Similarly many learning communities, such as MOOCs and other online learning environments, do not provide outlets for learners' products to become authentic. The PIs will combine data from MOOCs and online communities to discover groups of participants who behave in similar ways and investigate how to support the needs of these groups. This will lead to the proposed novel combined learning and work community that both provides support and offers authentic outlets for work products that are valued beyond a particular course.