STEM Graduate Training in Data Science: Solution-Oriented, Student-Led, Team-Based, Computationally-Enriched (SOLSTICE) Training

By Elena Naumova, PI

The SOLution-oriented, STudent-Initiated, Computationally-Enriched (SOLSTICE) approach was a teaching method for improving graduate student training in data intensive fields. The approach sought to improve students’ knowledge, skills, and attitudes in data sciences to solve complex problems, think critically, and effectively communicate across inter-generational, trans-disciplinary research teams. Using a data-intensive, project-based learning approach, graduate students worked collaboratively to design, evaluate, and disseminate research in team environments.

As data scientists, these students learned how to pose research questions, translate information into potential actions, develop data collection, analysis and visualization schemes and protocols, and exchange information, data methods, and results in a tailored manner to various audiences. Educational resources developed during this study will then be available for guiding faculty development and training process in the future.


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