The broader impact/commercial potential of this I-Corps project is to increase student and eventually, employee engagement, by better aligning skills and innate interests with degree programs, particularly novel STEM programs. In response to increasing demand for new types of jobs, degree programs such as Computational Genomics and Music Technology have combined fields that have historically been distinct. This project enables students to discover both traditional and emerging majors relevant to them. By providing actionable insights and better alignment of interests early on, this decreases the friction of changing majors (~80% currently) during college and begins to mitigate widespread lack of engagement (~70%) in the workplace. Compared with traditional methods that match GPAs, test scores, unstructured essays, and resumes, with schools, majors, and job openings, this project could revolutionize the way students identify, train and prepare for their future careers.
This I-Corps project is based on a novel patent-pending technology of a unified multi-dimensional data representation method called Skills Genome. Skills Genome can be exploited by several machine learning models, allowing for capturing and modeling complex student data inputs such as critical thinking, communication, interests, leadership, etc. with temporal graphs. By making the structure of the graph accessible to several machine learning models, the method improves accuracy, relevance and facilitates scale. Specifically, this tracks the student?s development timeline, so they can best determine the timing and sequencing of skills needed for their chosen careers. Further, by matching profiles at scale, new insights into potential careers can be surfaced, along with the next steps needed to achieve them.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
