Sociotechnical Interventions for Nurturing Successful Team Learning Experiences

随着工作场所协作需求的增加，教学团队合作对于帮助学生在所选职业中取得成功至关重要。想要将团队合作纳入课程的教师面临着挑战：如何将学生分组为给定学习目标的有效团队，以及一旦形成，如何支持队友连接以创建成功的学习体验。今天，教师努力解决这些挑战，往往委托团队形成的学生自己，并进行很少，如果有的话，旨在团队发展的活动。该项目将产生1）技术创新，使教师能够在算法上将学生分组为具有有效组成的团队，以实现学习目标; 2）干预活动，以培养团队合作的基础，如团队身份和这些团队的心理安全。这些活动和技术创新将受到相关理论的激励，通过与利益相关者的设计会议进行完善，并在大学课程中进行实证测试。项目成果有可能帮助分配团队项目的许多教师决定（1）如何最好地将学生分组到给定课程特定目标的团队中，（2）如何使用智能团队组建工具实现这些最佳团队，以及（3）如何帮助团队创造促进成功的心理安全。学生被分配到团队，他们可以最好地利用自己的个人优势，通过体验一个更公平的团队组建过程，并通过学习如何与队友最有效地参与，预计将受益。在本项目中，研究生将获得人机交互、学习科学和计算机科学方面的知识和技能，并将了解创建成功的网络学习工具所需的跨学科设计和研究过程。本项目在大型课程设置中调查新算法团队组建和社交技术的结合，以支持团队发展。该项目整合了社会和学习科学和技术设计，以促进以下方面的知识：（1）团队组成与协作过程、团队绩效和团队满意度之间的关系，以实现特定的学习目标;（2）学习者外包技术，以生成学生喜欢的团队组成，并让他们参与配置这些组成的团队形成工具;（3）采取干预措施，帮助团队为成功的学习经验奠定基础，并根据团队的组成和目标制定干预措施团队应执行的指导方针;以及（4）不同类别的学习者如何感知算法团队形成的价值和公平性，以及他们如何做出这种决定。这四个研究目标将通过一个基于设计的研究方法来解决，其中一个迭代的方法被应用到设计，部署和评估的技术和干预，从学习，团队组成和团队建设的理论绘图。研究工作将推进我们的知识，如何最好地支持协作学习活动，并朝着未来的进步，教师可以联合收割机结合社会进程和智能工具，提供有效的团队为基础的学习经验，为所有的学生。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

As the need for collaboration in the workplace increases, teaching teamwork is important for preparing students to be successful in their chosen careers. Instructors who want to incorporate teamwork into their courses face challenges: how to group students into effective teams given the learning goals and, once formed, how to support teammates in connecting to create a successful learning experience. Today, instructors struggle to address these challenges, often delegate team formation to the students themselves, and conduct few, if any, activities aimed at team development. This project will produce 1) technological innovations that will enable instructors to algorithmically group students into teams with effective compositions given the learning goals and 2) intervention activities to nurture the foundations of teamwork such as team identity and psychological safety in those teams. The activities and technological innovations will be motivated by relevant theories, refined through design sessions with stakeholders, and empirically tested in university courses. The project outcomes have the potential to help the many instructors assigning team projects decide (1) how to best group students into teams given the context-specific goals of a course, (2) how to achieve those best groups with an intelligent team formation tool, and (3) how to help teams create the psychological safety that fosters success. Students are expected to benefit by being assigned to teams where they can best utilize their individual strengths, by experiencing a fairer team formation process, and by learning how to engage with teammates most effectively. Graduate students aiding the research activities in this project will gain knowledge and skills in human-computer interaction, learning science, and computer science, and will learn about the interdisciplinary design and research process necessary to create successful cyberlearning tools.This project investigates, in large course settings, a conjunction of new algorithmic team formation and social techniques, to support team development. The project integrates social and learning science and technology design to advance knowledge of (1) how team composition relates to collaborative process, team performance, and team satisfaction for specific learning goals; (2) learnersourcing techniques to generate team compositions that students prefer and to involve them in configuring these compositions in a team formation tool; (3) interventions to help a team develop foundations for successful learning experiences and guidelines for which interventions teams should perform, given the team’s composition and goals; and (4) how different categories of learners perceive the value and fairness of algorithmic team formation and how they make that determination. These four research goals will be addressed through a design-based research methodology—where an iterative approach is applied to the design, deployment, and evaluation of both the technology and the interventions—drawing from theories of learning, team composition, and team building. The research efforts will advance our knowledge of how best to support collaborative learning activities and progress toward a future where instructors can combine social processes and intelligent tools to deliver effective team-based learning experiences for all students.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.