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Introducing Data Science to School Kids

Data-driven decision making is fast becoming a necessary skill in jobs across the board. The industry today uses analytics and machine learning to get useful insights from a wealth of digital information in order to make decisions. With data science becoming an important skill needed in varying degrees of complexity by the workforce of the near future, we felt the need to expose school-goers to its power through a hands-on exercise. We organized a half-day long data science tutorial for kids in grades 5 through 9 (10-15 years old). Our aim was to expose them to the full cycle of a typical supervised learning approach - data collection, data entry, data visualization, feature engineering, model building, model testing and data permissions. We discuss herein the design choices made while developing the dataset, the method and the pedagogy for the tutorial. These choices aimed to maximize student engagement while ensuring minimal pre-requisite knowledge. This was a challenging task given that we limited the pre-requisites for the kids to the knowledge of counting, addition, percentages, comparisons and a basic exposure to operating computers. By designing an exercise with the stated principles, we were able to provide to kids an exciting, hands-on introduction to data science, as confirmed by their experiences. To the best of the authors' knowledge, the tutorial was the first of its kind. Considering the positive reception of such a tutorial, we hope that educators across the world are encouraged to introduce data science in their respective curricula for high-schoolers and are able to use the principles laid out in this work to build full-fledged courses.