Inspiration

We saw that the under representation of women in the STEM field starts at childhood. We were inspired and humbled by the stories of women who revolutionized STEM yet are seldom discussed and known. To bring the knowledge of these women to young girls that may doubt themselves or have already dismissed a potential future in STEM is something that we feel is an important step forward in causing a cultural change.

What it does

Our 'flashcards' display profiles of influential women in the history of STEM: mathematicians, computer scientists, engineers, inventors, physicist, biologists, and other STEM related fields. It also displays profiles of contemporary women and provides a platform to connect young girls to these women through a direct messaging service as a form of mentorship. We try to match the profiles of the women with interests that young girls have provided.

How we built it

We used Firebase for the back-end (authentication and jSON storage). The front-end was built using ReactJS and Material Design. The application was embedded in an iOS application via Swift.

Challenges we ran into

We attempted to incorporate IBM's Node Red Natural Language Understanding to analyze the profiles of the girls against sourced links. The idea was clear in theory, but we ran into walls on the execution. The final result is a demonstration of a possible filtering scheme that can be implemented.

Accomplishments that we're proud of

We are proud that we were able to work as a team and get a functional application up and running. We are proud that of being allies in the movement to bring more young girls into STEM and hopefully come closer to closing the gender gap in our field.

What we learned

We learned that sometimes implementations of ideas that sound good in theory are not always so straightforward. Even simple modifications required careful understanding of how pieces came together to ensure the best possible user experience. We also had to imagine using the application from the perspective of young girls so that was a good thought exercise in UI design.

What's next for iAm

Extensions of iAM can incorporate Natural Language Understanding and IBM Watson Discovery to automatically populate our database with profiles of women in STEM, and provide closer matches of profiles to the interests of girls using the application. Looking into getting volunteers to act as mentors through there profiles would also be a worthwhile endeavor.

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