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We invite research and practice papers that address the “convergence of communities” in lak and bring a novel perspective and approach for reflecting on the field. We design several feature tables and compare the performance of six machine learning models on these feature tables. We demonstrate how existing mooc dropout prediction pipelines can be made interpretable, all while having predictive performance close to existing techniques.
