Hunter Glanz (Cal Poly San Luis Obispo)
Abstract
While content in data science courses and programs continues to crystallize, a few things have become abundantly clear. Chief among them is the noticeable increase in hands-on work with data to wrangle it, visualize it, and analyze it compared to historically traditional statistics courses. In particular, using software to perform these operations and experience every part of the data science life cycle. Whether it’s a spreadsheet tool or a coding language, students struggle with this increased data handling. We propose a scaffolded approach to teaching, assessing and practicing these data skills using one or a combination of software tools. By giving students the introduction and resources to use software, and then strategically revising those resources for subsequent activities the students receive a well-curated and properly supported educational experience. This foundation allows students to develop essential data skills that they can use for the rest of their lives.