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.
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A Teaching Routine for Working With Existing Data in Science Classrooms
Working with existing data is central to science investigations, but students and educators have generally not had experience using existing data sets to answer their own questions. We introduce a teaching routine that makes explicit critical steps in the process of working with data to gain insight into real-world phenomena. We intend the routine to support both curriculum developers and teachers in designing and enacting lessons to support students in engaging productively with scientific data, focusing on steps that are not commonly encountered in science classes.
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- PAR ID:
- 10541544
- Editor(s):
- Blikstein, Paolo; Van_Aalst, Jan; Kizito, Rita; Brennan, Karen
- Publisher / Repository:
- International Society of the Learning Sciences
- Date Published:
- Page Range / eLocation ID:
- 1859 to 1860
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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