{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/enabling-end-to-end-machine-learning","title":"Enabling End-To-End Machine Learning Replicability: A Case Study in Educational Data Mining","arxiv_id":"1806.05208","date":"2018-06-13","proceeding":null,"authors":["Josh Gardner","Yuming Yang","Ryan Baker","Christopher Brooks"],"abstract":"The use of machine learning techniques has expanded in education research, driven by the rich data from digital learning environments and institutional data warehouses. 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