Our project is building an intelligent chatbot and using crowdsourced mentoring to support low-income high school students’ enrollment in college.
The goal of this project is to test a mentorship model for extending advising to college-accepted, low-income high school students during the summer months after graduation. Prior research has documented a pattern of “summer melt” in which motivated and academically-prepared high school graduates who have been accepted to college decide not to enroll in college. Summer melt is especially prevalent among low-income, African American, and Latinx students. Through prior research, the partnership team identified a set of barriers that contribute to summer melt for New York City (NYC) high school students and concluded that combining the transmission of college knowledge with support for students' development of college-bound identity is a potential solution to this problem. This project will explore how to scale mentorship via a text-messaging application that incorporates social and emotional supports and coordinates personal interactions between students and a large team (or “crowd”) of mentors
PIs: Alisha Ali, Bruce Homer, June Ahn (UC Irvine)
Ober, T. M., Ahn, J., Ali, A., Moner, A., Azam, A., Ramos, N., & Homer, B. D. (in press). A mixed-methods analysis of mechanisms that support college enrollment among low-income and first generation high school students. Translational Issues in Psychological Science.