Remote teaching data-driven physical modeling through a COVID-19 open-ended data challenge

Physics can be seen as a conceptual approach to scientific problems, method for discovery, but teaching this aspect of our discipline challenge. We report on first-time remote experience computational physics third-year laboratory class taught in the first part 2020 COVID-19 pandemic (March-May 2020). To convey ``physics data" data analysis and data-driven physical modeling we used interdisciplinary sources, with an openended ``COVID-19 challenge" project core course. epidemiological provided ideal setting motivating students deal complex where there is no unique or preconceived solution. Our results indicate that such problems yield qualitatively different improvements compared close-ended projects, well point critical aspects using these strategy. By breaking students' expectations unidirectionality, unexpected opportunities promote active work learning.