Ployem

To give URM students the confidence to pursue tech and education, we create opportunities and access for them to learn hands-on technical skills, mentorship, practical experience, and be offered internships.

The number of well-paid jobs in the tech sector has been growing exponentially, and will continue to do so. If we can help URM students gain confidence and see themselves in those positions, then we can motivate them to both complete high school and attend college, thereby improving education outcomes for schools across the board.

Our solution is a three-step model: a learning stage, practical hands-on experience, resulting in an internship. We will provide undergraduate mentors during the learning stage to play a TA-like role, via discussion forums like Piazza to answer questions, and weekly office hour/discussion sessions.

At the completion of the course, they will have gained the skills necessary to take on hands-on projects in teams, with continued coaching and guidance from the mentors. To make the experience even more impactful, we will offer internships at our own company, as mentors for the next cohort of students.

High schools throughout the US are looking to increase their graduation and college attendance rates, and in particular, address the disparity in rates between different racial and socio-economic demographics. For schools to solve this issue, however, students need guidance and access to resources teaching them how to use their education to advance their careers. Yet, while 83% of teens are thinking about their educational and career path weekly, 73% are unsure how to use their education to develop their career and many are unaware of affordable options.

Specifically, students from underrepresented minority (URM) groups do not see themselves in software or other degree-requiring roles because they don’t see the benefits of going to college, and lack the guidance and resources to gain these technical skills. This translates to only 88% of high school students graduating and only 60% going to college, and these numbers vary greatly based on socio-economic status.

Imagine being an eighteen year old in the United States -- yes, it's terrifying. You are constantly thinking of "what college will I go to?", "how will I even make it college?", "will I be able to find a job quickly after college?", "how can I showcase myself when I'm too busy working to support my family?", "is college even worth it then?". These are all questions URM high school students are constantly thinking of. Unfortunately, it's often very hard for them to find a guidance. An assurance that someone / something is there to help guide them and remain there as something they can always lean on. Enter Ployem. Ployem is a never ending cycle of learning and working. High school students undergo 3-4 months of prep then apply their skills in the next 1-2 months, then can either get a job or come back into a higher cycle. Previous members mentor newer members, what this creates is immediate visible results. It shows students how what they learn translates into the real world. This then translates into them understanding the value of education and might help them pursue further education even if they are supporting their families. They will have experienced first-hand this is a better way to support their family and themselves in the long run. 

We have done some preliminary research by just reading articles, attending conferences and meetings. We aim to continue to do some more research, which is why we are applying to all the programs we can. On the team all members have worked for at least a year at a high school teaching center and have experience working from UMRs. It was our experiences that led us to want to solve this issue.

We have semi-developed an educational site, (https://www.ployem.com), have met and attended several conferences such as the Futures of Education Conference (that was today haha). 

Our technology is 2 parts: a resource aggregator and student-resource matching algorithm. The resource aggregator will be like a giant crawler that finds, filters and organizes existing online educational content. This process is quite straightforward on a high-level but much more tedious to implement. On a lower-level, the algorithm has 3 layers: a find layer, which just finds and scraps sites like khan academy, youtube videos. Then theres the filtering layer, which (can use ML) decide what content is meaningful, and finally organizer uses existing techniques like VQA to group the filtered content. Now we are ready for the second half: the matching algorithm. On a high-level: every student will be matched with some organized filtered content based on their current ability. Modern techniques for matching are unfortunately very weak as they rely heavily on user inputted data. Our algorithm will focus on non-opinionated data (like transcripts, evaluations, online presence, and other similar facts). While the kind of inputted data we plan on changing, we can still use existing matching models (will be difficult as most platforms do not open source their matching algorithms). The biggest perk is we will provide usage free of charge. Our target are individuals who suffer specifically because of the price tag and by providing this technology for free will completely reshape how they view education.

We plan on starting with a small cohort. Preferably around 50-100 students, that is because we don't want to start too big and at the same time we want to be able to easily make any updates or changes to the structure. We also want to ensure we have enough mentors for the students during the first cohort.

Our impact goals is simple: make sure kids go "wow, this was cool" after their first cycle through the program and be ready to signup for the next cycle. This will validate: the technology we develop and the philosophy we are using. 

One indicator that we are working towards our goal is the development of the platform. While that will be a challenge, if that is made then the next milestones will be easier to carry out. We would have a month of reachout to get students and then after a month monitor their progress, after 2 months give a small mock project and after three months be ready for the projects and by the end of the 4th month, analyze the results of the experiment.

Time. Most team members right now are MIT students and MIT classes are hard and time-consuming. That is why it will take probably most if not all the Spring Semester to develop the technology and maybe even extend into the summer.

3 of us are CS majors with experience working with web-development and ML. This is crucial to the development of the platform and it helps ensure that whatever solution we come up with we know is feasible. We all have experience working with URM high school students and some of us have were URM high school students, so we have first-hand experience with the needs and thinking of URM students. One of us is also completing research at MIT and currently is very involved with educational institutions and has connections with different organizations such as Russian Math School and a free tutoring program for immigrant and UNRM students. Another member of our team has developed software educational tools before and another 2 has experience developing, training, and employing ML models for matching purposes. 

N/A