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The ASCCR Frame for Learning Essential Collaboration Skills

机译:学习基本协作技能的ASCCR框架

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Statistics and data science are especially collaborative disciplines that typically require practitioners to interact with many different people or groups. Consequently, interdisciplinary collaboration skills are part of the personal and professional skills essential for success as an applied statistician or data scientist. These skills are learnable and teachable, and learning and improving collaboration skills provides a way to enhance one’s practice of statistics and data science. To help individuals learn these skills and organizations to teach them, we have developed a framework covering five essential components of statistical collaboration: Attitude, Structure, Content, Communication, and Relationship. We call this the ASCCR Frame. This framework can be incorporated into formal training programs in the classroom or on the job and can also be used by individuals through self-study. We show how this framework can be applied specifically to statisticians and data scientists to improve their collaboration skills and their interdisciplinary impact. We believe that the ASCCR Frame can help organize and stimulate research and teaching in interdisciplinary collaboration and call on individuals and organizations to begin generating evidence regarding its effectiveness.
机译:统计和数据科学尤其是协作学科,通常要求从业人员与许多不同的人或群体进行互动。因此,跨学科的协作技能是成功应用统计学家或数据科学家必不可少的个人和专业技能的一部分。这些技能是可学且可教的,学习和改善协作技能可提供一种增强统计和数据科学实践的方法。为了帮助个人学习这些技能,并帮助组织学习这些技能,我们开发了一个框架,涵盖了统计协作的五个基本组成部分:态度,结构,内容,沟通和关系。我们称其为ASCCR框架。该框架可以并入教室或工作中的正式培训计划中,也可以由个人通过自学使用。我们展示了如何将该框架专门应用于统计学家和数据科学家,以提高他们的协作技能和跨学科影响。我们认为,ASCCR框架可以帮助组织和激发跨学科合作中的研究和教学,并呼吁个人和组织开始就其有效性产生证据。

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