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As demand for data scientists has increased to inform decision-making across multiple fields of societal importance, postsecondary institutions have expanded data science course offerings. Despite such growth, educators struggle to teach students all the skills central to data science. They focus on programming and statistical tools and lack time for mentoring students in data storytelling. This working paper reviewed literature and interviewed experts to model the domain knowledge of data storytelling to inform the design of intelligent technology to support data storytelling instruction at scale. The paper closes with a recommendation of two ways that artificial intelligence tools can support the development of students’ data storytelling knowledge and skills: "direct" feedback to students on routine data science tasks and "facilitated" summaries of students' data story progress to inform instructors' feedback. We intend to apply these insights to the design of intelligent coaching in an online platform to support the development of storytelling competency at scale. 

Data storytelling is the skill to communicate data effectively and efficiently. Effective data storytelling goes beyond data visualization and focuses on explanation with clear rhetorical functions. It starts with a set of data insights collected from the data science workflow and involves iterative and interactive processes of filtering those insights into story slices, from which data stories can be created through ordering, organizing and narration. Data storytelling is an integral component of a well-rounded data science education, which complements foundational skills like quantitative reasoning and programming. Despite its significance, solid understanding of the theory and practice of developing data storytelling competency is lacking. Data storytelling is often perceived as a mythical process where quantitative information magically transforms into compelling narratives. Designing scalable coaching tools for data storytelling requires leveraging multidisciplinary expertise from learning science, computer science, data science, communication science, and human-centered design. In this workshop, we will share some initial findings and reflections from our interdisciplinary team searching for effective coaching methods and tools to support coaching data storytelling at scale. We will present results from literature reviews and expert interviews which will be packaged into a set of foundational tools such as mental model, cognitive processes and schema for story construction, assessment strategy, as well as preliminary ideas of tools to support data storytelling coaching. We hope to use this workshop to build a community of researchers and practitioners in coaching data storytelling in postsecondary formal and informal learning context.