This past October 7-11, STEMscopes’ Dr. Carlos Monroy, Data Scientist with Rice University Center for Digital Learning and Scholarship, was one of twenty-nine selected to participate in the The National Science Foundation’s Ideas Lab workshop titled: Data-Intensive Research to Improve Teaching and Learning. This five-day long workshop aims to foster novel, transformative, multidisciplinary approaches to tackle how best to teach STEM in terms of producing student results. The NSF took a unique approach by recruiting not only educators but also practitioners from a wide range of disciplines and institutions.
In collaboration with scholars from Brown University, New Mexico State University and ETS, Dr. Monroy’s group proposed a proof of concept named Learninformatics to improve the way in which teachers teach STEM disciplines. Learninformatics takes a similar approach as the one Bioinformatics does in Biology and Biochemistry. With the use of information visualization, computing algorithms, psychometrics and pedagogy principles we aim at mapping learning pathways, that is, the method in which students go from “not knowing” to mastering knowledge on concepts and skills – for informing teachers in the development of effective scaffolding activities and curricular interventions to produce specific results (e.g. scoring advanced on an AP exam or passing the 8th grade STAAR™). Data mining at this level may eventually reveal that teaching a specific STEM subject with a game, hands-on investigation, or virtual simulation inherently produces better results that other teaching methods.