SBIR Phase I: The Smart Study Recommendations Engine

This SBIR Phase I project is focused on continued development of a software platform that is used by students for peer to peer homework and studying help. After school help has historically been delivered by tutors and homework hotlines but those avenues have been proven to be inadequate in closing learning gaps for students after they exit the classroom. The proposed technology is expected to further democratize homework and studying help. Being peer to peer, the proposed technology can radically shrink the cost of personalized homework and studying help for students at their own time and pace - especially the ones from economically or socially more challenged backgrounds. The project will also explore use of an innovative business model to optimize commercial viability with impacting a broad range of students irrespective of their backgrounds. It is expected that when fully developed, the technology would emerge as a scalable low-cost option to help improve student learning outcomes both nationally and globally. The key intellectual merit of this project is in the development of a Smart Study Recommendations Engine. This involves harvesting the data from the class notes uploaded by students, analyze it to surface predictive insights and automatically deliver the notes or wide-ranging peer-reviewed study materials directly to the student users based on their learning styles, learning abilities, and learning gaps, without requiring them to perform a search. It will also provide them with an ability to connect them with peers who can provide additional support. Thus, this project seeks to provide personalized study playlists based on a student profile and pair them with a peer mentor who can provide deeper clarifications as required. The key outcome to be demonstrated is that 1 in 5 students engages favorably with the auto delivered math notes, helped by a peer who can provide clarity and tutoring as needed. 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.