Synthesis and Design Workshop: Digitally-Mediated Team Learning

该项目将召集一个由研究人员、教育工作者和实践者参加的研讨会，以推进科学、技术、工程和数学（STEM）学科中技术增强团队学习的变革性教学方法。研讨会将通过重点关注促进数字媒介团队学习的教学技术，提高下一代学习架构的利用率和效率。跨学科科学和工程研究人员、开发人员和教育工作者将确定近期和未来的研究方向，以促进适应性强的数字环境，实现高效、有益和可扩展的基于团队的学习。研讨会将通过自动化识别和利用学习者的效率和知识差距来强调不同学习者之间合作的个性化，以创建互补的协作团队，最大限度地提高同伴教学和学习的途径。该研讨会将促进国家和社会的目标，即改善STEM教学，培养更强大的国家STEM劳动力，同时联合数据分析、数据挖掘和教学设计与技术方面的专家。研讨会的成果将通过社会、传统和大众媒体传播，研讨会的成果将惠及多个学科的研究人员、教育工作者和从业者，同时为数字化增强的以学习者为中心的学习方法提供信息。该项目将侧重于以下技术目标：(1)确定学习分析方面的新研究，以使学习者设计团队的组成、形成和适应更加优化；(2)发现物理和虚拟学习环境的进步，可以实现对学习者团队更有效和可扩展的实时观察和评估；(3)区分数据挖掘技术，利用监视器、跟踪器和自动相机观察等设备来提高团队学习的效率；(4)扩展协作学习技术，以扩大不同学习者群体的参与和成就，包括妇女和其他代表性不足和服务不足的人群。在研讨会之前，论文征集将征求提交专业知识简介和职位摘要。在为期两天的研讨会期间，与会者将有机会参加海报会议、主题演讲、小组会议、技术分组会议和行动委员会。研讨会的结果将是1年、3年和5年以上的研究和发展计划，这些计划被组织成每个技术重点的轨道。除了社交媒体和大众媒体外，传播活动还将包括白皮书、执行摘要、信息图表和面向公众的网站，以最大限度地实现为数字媒介团队的设计、开发、实施和评估提供统一路线图的目标，从而提高所有学习者的成就。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。

This project will convene a workshop of researchers, educators, and practitioners to advance transformative pedagogical approaches for technology-enhanced team learning within science, technology, engineering, and math (STEM) disciplines. The workshop will advance the utilization and efficacy of next-generation learning architectures through a focus on instructional technologies that facilitate digitally-mediated team-based learning. Interdisciplinary science and engineering researchers, developers, and educators will identify near-term and future research directions to facilitate adaptable digital environments for highly-effective, rewarding, and scalable team-based learning. The workshop will emphasize personalization of collaborations among diverse learners by automating the identification and utilization of learners' efficacies and knowledge gaps to create complementary collaborative teams that maximize avenues for peer teaching and learning. The workshop will advance both national and societal goals of improving STEM instruction to develop a stronger national STEM workforce, while uniting experts in data analytics, data mining, and instructional design & technology. Dissemination of the findings from the workshop will include social, traditional, and popular media outlets, and the outcomes of the workshop will benefit researchers, educators, and practitioners from multiple disciplines, while informing digitally-enhanced learner-centered approaches to learning.The project will focus on technical objectives of: (1) identifying new research in learning analytics required to automate more optimal composition, formation, and adaptation of learner design teams; (2) detecting advances in physical and virtual learning environments that can achieve more effective and scalable observation and assessment of learner teams in real-time; (3) distinguishing data mining techniques to leverage devices such as monitors, trackers, and automated camera observations to increase efficacy of team learning; and (4) extending collaborative learning technologies to broaden participation and achievement of diverse learner groups, including women and other underrepresented and underserved populations in STEM. Prior to the workshop, a call for papers will solicit submission of an expertise profile and position abstract. During the two-day workshop, participants will be afforded opportunities to participate in a poster session, keynote, panel session, breakout technical sessions, and action committees. The workshop will result in 1-, 3-, and 5+ year research and development plans organized into tracks for each technical focus. In addition to social and popular media, dissemination activities will include a white paper, executive summary, infographics, and public-facing website to maximize the outreach towards the goal of providing a unifying roadmap for the design, development, implementation, and evaluation of digitally-mediated teams advancing the achievement of all learners.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.