Kaggle Competitions in the Classroom: Retrospectives and Recommendations

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Institute for Operations Research and the Management Sciences (INFORMS)
After increasing our course offerings in data science and machine learning at the United States Military Academy at West Point, we have been investigating innovative ways to motivate our students to engage with this challenging material and explore data outside the classroom. In addition, with the move to virtual classes and students spread across numerous time zones, we needed to find additional ways to build community and leverage our networks to add a flair to our teaching beyond the traditional in-class assessments. We found one such opportunity in Kaggle’s ability to host private competitions for educators. Kaggle is an online data science platform best known for its public machine learning competitions. Since its inception in 2008, Kaggle has hosted thousands of competitions to advance research on a myriad of topics ranging from satellite imagery feature detection [1] to COVID-19 research analysis [2]. Besides hosting these global competitions, Kaggle has grown into an expansive data science educational platform that offers full courses, an open-source dataset repository, and a feature known as Kaggle InClass competitions (KICs) [3]. These KICs are contests specifically tailored for use in an academic setting that are completely customizable by the hosting professor or teaching assistant. In turn, the Kaggle platform provides a leaderboard, centralized location to access the competition data, and support for various popular code libraries.
Kaggle Classroom Competitions, data science, virtual learning online learning
King et al., “Kaggle Competitions in the Classroom.” 2020.