Creating Shared Understanding in Statistics and Data Science Collaborations

• Published in: Journal of Statistics and Data Science Education Vol. 30; no. 1; pp. 54 - 64
• Main Authors: Vance, Eric A., Alzen, Jessica L., Smith, Heather S.
• Format: Journal Article
• Language: English
• Published: Alexandria Taylor & Francis 2022; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Applied mathematics; Capstone Experiences; Collaboration; Common knowledge; Communication; Communication Skills; Consulting; Cooperation; Data Analysis; Data science; Doubtful understanding; Expertise; Interdisciplinary Approach; Interdisciplinary aspects; Knowledge; Laboratories; Mathematics Education; Misconceptions; Science Curriculum; Science education; Science Instruction; Scientists; Skills; Statistical analysis; Statistical Data; Statistical practice; Statistics Education; Subject specialists; Teaching; Teaching Methods
• ISSN: 2693-9169; 2693-9169
• DOI: 10.1080/26939169.2022.2035286

Statisticians and data scientists have been called upon to increase the impact they have through their collaborative projects. Statistics and data science practitioners and their educators can achieve and enable greater impact by learning how to create shared understanding with their collaborators as well as teaching this concept to their students, colleagues, and mentees. In this article, we explore and explain the concepts of common knowledge and shared understanding, which is the basis for action to accomplish greater impacts. We also explore related concepts of misunderstanding and doubtful understanding. We describe a process for teaching oneself and others how to create shared understanding. We conclude that incorporating the concept of shared understanding into one's practice of statistics or data science and following the steps described will result in having more impact on projects and throughout one's career.