Synthesis and Design Workshop: Digitally-Mediated Team Learning

该项目将召开一次研究人员、教育工作者和实践者的研讨会，以推进科学、技术、工程和数学(STEM)学科中技术增强型团队学习的变革性教学方法。讲习班将通过侧重于促进以数字为媒介的基于团队的学习的教学技术，提高下一代学习架构的利用率和效率。跨学科的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，以促进适应的数字环境，实现高效、有价值和可扩展的基于团队的学习。讲习班将强调不同学习者之间协作的个人化，方法是自动确定和利用学习者的效率和知识差距，以创建互补的协作团队，最大限度地扩大同伴教学和学习的途径。研讨会将推进改善STEM教学的国家和社会目标，以培养一支更强大的国家STEM劳动力队伍，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。研讨会结果的传播将包括社交、传统和流行媒体渠道，研讨会的结果将使来自多个学科的研究人员、教育工作者和实践者受益，同时告知数字增强的以学习者为中心的学习方法。项目将集中于以下技术目标：(1)确定学习分析中需要的新研究，以自动化更优化的学习者设计团队的组成、形成和适应；(2)检测物理和虚拟学习环境的进展，以实现对学习者团队的更有效和可扩展的实时观察和评估；(3)区别数据挖掘技术，以利用监视器、跟踪器和自动摄像机观察等设备来提高团队学习的效率；以及(4)扩展协作学习技术，以扩大不同学习群体的参与和成就，包括妇女和STEM中其他代表性不足和服务不足的群体。在研讨会之前，论文征集将征集专家简介和职位摘要的提交。在为期两天的研讨会期间，参与者将有机会参加海报会议、主题演讲、小组会议、分组技术会议和行动委员会。研讨会将为每个技术重点制定1年、3年和5年以上的研究和开发计划。除了社交和流行媒体，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，以最大限度地扩大宣传范围，以实现为促进所有学习者的成就的数字中介团队的设计、开发、实施和评估提供统一路线图的目标。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.