CHS: Small: Novel Technology Augmented Methods to Improve Team-based Engineering Education for Diverse Teams
CHS:小型:新技术增强方法可改善多元化团队的团队工程教育
基本信息
- 批准号:1910117
- 负责人:
- 金额:$ 49.81万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-08-01 至 2024-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This project will develop an automated system to measure core team processes. Teams are increasingly prevalent in today's workforce, and the ability to work effectively in teams is a competitive advantage. As a result, team-based learning is now widespread in universities across all levels, ranging from first-year engineering design courses to senior capstone projects. The rise of team-based learning has created two inter-related challenges in effectively delivering the optimal benefits of this learning modality. First, while educators have matured in evaluating technical learning, such as quality of results and presentation, they are still in the early stages of understanding, measuring, and educating students on the process of effective teamwork itself. Second, team-based research relies almost exclusively on self-report measures and human observation, which are error prone and problematic. Thus, there is a clear need to augment current methods so scientists and educators can better measure the processes that lead to effective team performance. The project will impact not only team-based education, but behavioral sciences more broadly. By developing methods to objectively measure behavioral correlates of important psychological constructs, behavioral sciences will go beyond the traditional tools for research.Grounded in psychological theory and research, and enabled by advances in engineering, this research will leverage two forms of team interactions to understand key metrics related to individual effectiveness, team dynamics, and the impact of diversity on both individual and team metrics: (1) in-person interactions measured from the audio-visual recordings of team meetings, and (2) work interactions measured from team's shared written online collaborative documents. The system developed through this research will include novel methods to extract action sequences from audio-visual meeting data and from the online documents. Data will be collected in a series of projects across three team environments: (1) targeted studies where teams are formed for 90-minute project sprints; (2) medium-term teams working on a 7-week engineering design internship, and (3) longer-term teams in a semester-long engineering design course. Validated psychological assessments and new metrics will be collected and assembled into an extensive and diverse dataset. A multilayer network model will be developed to represent the different modes of human interaction collected in the individual action sequences. The objective is to extract network features that correlate with meaningful psychological indicators of team dynamics and role emergence within teams.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.
该项目将开发一个自动化系统来衡量核心团队流程。 团队在当今的劳动力中越来越普遍,在团队中有效工作的能力是一种竞争优势。因此,基于团队的学习现在在各个级别的大学中广泛存在,从第一年的工程设计课程到高级顶点项目。团队学习的兴起给有效实现这种学习方式的最佳效益带来了两个相互关联的挑战。首先,虽然教育工作者在评估技术学习(例如结果和演示的质量)方面已经成熟,但他们仍处于理解、衡量和教育学生有效团队合作过程本身的早期阶段。其次,基于团队的研究几乎完全依赖于自我报告措施和人类观察,这容易出错且存在问题。因此,显然需要增强现有方法,以便科学家和教育工作者能够更好地衡量导致有效团队绩效的过程。该项目不仅会影响基于团队的教育,还会影响更广泛的行为科学。通过开发客观测量重要心理结构的行为相关性的方法,行为科学将超越传统的研究工具。以心理学理论和研究为基础,并以工程学的进步为基础,本研究将利用两种形式的团队互动来了解与个人有效性、团队动态以及多样性对个人和团队指标的影响相关的关键指标:(1)从团队的视听记录中衡量的面对面互动 会议,以及 (2) 根据团队共享的书面在线协作文档衡量的工作交互。通过这项研究开发的系统将包括从视听会议数据和在线文档中提取动作序列的新方法。 数据将在三个团队环境中的一系列项目中收集:(1)有针对性的研究,组建团队进行 90 分钟的项目冲刺; (2) 中期团队进行为期 7 周的工程设计实习,(3) 长期团队进行为期一学期的工程设计课程。经过验证的心理评估和新指标将被收集并组装成广泛且多样化的数据集。将开发多层网络模型来表示在各个动作序列中收集的人类交互的不同模式。其目标是提取与团队动态和团队内角色出现的有意义的心理指标相关的网络特征。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
How Approaches to Animal Swarm Intelligence Can Improve the Study of Collective Intelligence in Human Teams
- DOI:10.3390/jintelligence8010009
- 发表时间:2020-03
- 期刊:
- 影响因子:3.5
- 作者:Lisa O'Bryan;M. Beier;Eduardo Salas
- 通讯作者:Lisa O'Bryan;M. Beier;Eduardo Salas
Objective Communication Patterns Associated With Team Member Effectiveness in Real-World Virtual Teams
- DOI:10.1177/00187208221147341
- 发表时间:2022-12-22
- 期刊:
- 影响因子:3.3
- 作者:O'Bryan,Lisa;Oxendahl,Tim;Sabharwal,Ashutosh
- 通讯作者:Sabharwal,Ashutosh
Conversational turn-taking as a stochastic process on networks.
对话轮流是网络上的随机过程。
- DOI:
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:O’Bryan, L.
- 通讯作者:O’Bryan, L.
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Margaret Beier其他文献
Margaret Beier的其他文献
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