MentorSpace

Empowering women in engineering through personalized mentor-mentee connections.

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Inspiration

In 2023, only 13.7% of the global engineering workforce were women. Women in engineering are forced to navigate an industry that doesn’t always value their skills, talents, and stories. There is a notable lack of female role models and mentors, further discouraging girls from pursuing engineering. Furthermore, it is not always easy to access or engage with the female engineering mentors who do exist.

Current mentorship programs exist to bridge the gender gap, such as within student organizations and companies. However, notable challenges include being smaller-scale (e.g. employees in a company or students at a specific college), requiring payment for services, and having no rankings of compatibility between mentors and mentees.

Thus, we created MentorSpace—a platform designed to empower women in engineering by matching you with the ideal mentor.

What it does

MentorSpace is designed to create personalized connections between mentees and mentors by automatically matching based on factors like academic major, career aspirations, and relatability. Mentees will no longer need to sift through endless lists of mentors or experience fading relationships with overly busy upperclassmen. By simply signing up and filling out a form, mentees have free access to an international pool of female role models.

Our matching algorithm ensures that mentees can connect with mentors who understand their journey, challenges, and aspirations. We show mentees the mentors that are their top 3 matches, allowing them to choose in case of error. By fostering these relationships, we aim to bridge the gender gap and pave the way for a more diverse and inclusive future in engineering.

How we built it

  • React for the frontend
  • Gemini-1.5-flash, MongoDB, Node.js, Insomnia, and JavaScript for the backend
  • Kinde for login/signup
  • Figma and IbisPaintx for design

Challenges we ran into

  • The first challenge we ran into was designing and implementing a matching algorithm that analyzes the mentee's responses and compares them with mentor profiles to determine compatibility. It was challenging training Gemini-1.5-flash to properly judge and assign compatibility based on words and abstract ideas, but after iterations of testing, revising the engineering prompt, and analyzing the data ourselves we were able to get reliable results.
  • Another challenge we encountered was linking the output string from Gemini-1.5-flash to our frontend components. After multiple console.log print-outs and researching how navigation worked in React, we were eventually able to get the state of a component transferred to another one, where the state could then be parsed and displayed.
  • We also encountered difficulties with routing, as we wanted to create a very specific user flow to make the process of signing up to be a mentee as intuitive as possible, but we were building from scratch with limited experience in this area.

Accomplishments that we're proud of

  • It was most of our team’s first time using React, so we’re glad to be able to learn and apply React to link the different components, have them integrate with the backend, and develop a functioning website!
  • Getting the user login and signup with Google to work, as it was also our first time working with proper authentication
  • Coding a matching algorithm that can rank mentors based on the mentee’s needs and wants
  • Cool landing page :)
  • Developing a product that we would use ourselves!

What we learned

We learned how to:

  • implement user authentication into an already existing codebase using Kinde
  • interact with the MongoDB Database and retrieve and parse data from the database
  • find efficient ways to test and improve our AI-generated model using Insomnia
  • how to leverage React’s components to design the flow of MentorSpace

What's next for MentorSpace

  • Increasing the scalability of MentorSpace by expanding the audience to beyond women in engineering (e.g. physical sciences, business, policy)
  • Implementing a feedback feature where mentees/mentors can put in anonymous (or not anonymous if they prefer) feedback or shared experiences about anything, further stimulating a safe and warm space
  • Further personalizing the matching algorithm by allowing mentees to select the priority of each of the criteria

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