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How an Artificially Intelligent Virtual Assistant Helps Students Navigate the Road to College

30 Pages Posted: 25 Mar 2017  

Lindsay C. Page

University of Pittsburgh School of Education

Hunter Gehlbach

University of California, Santa Barbara

Date Written: March 24, 2017

Abstract

Deep reinforcement learning using convolutional neural networks is the driving technology behind autonomous vehicles. We apply this same technology to a different journey: the summer transition from high school to college. After being accepted, students must navigate a host of well-defined but often challenging tasks prior to college matriculation. We employ conversational artificial intelligence (AI) to efficiently support thousands of would-be college freshmen by providing personalized, text-message based outreach and guidance for each task where they needed support. We implement this system in the context of a field experiment with Georgia State University (GSU). GSU-committed students assigned to the treatment exhibited greater success with pre-enrollment requirements and were 3.3 percentage points more likely to enroll. These impacts parallel prior interventions but with far less burden on university staff. Given the capacity for AI to learn over time, this intervention has promise for providing personalized college transition guidance at scale.

Keywords: Artifical intelligence; college access; summer melt; randomized controlled trial

JEL Classification: I20, I21

Suggested Citation

Page, Lindsay C. and Gehlbach, Hunter, How an Artificially Intelligent Virtual Assistant Helps Students Navigate the Road to College (March 24, 2017). Available at SSRN: https://ssrn.com/abstract=2940297

Lindsay C. Page (Contact Author)

University of Pittsburgh School of Education ( email )

Pittsburgh, PA 15260
United States
412-648-7166 (Phone)

Hunter Gehlbach

University of California, Santa Barbara ( email )

Santa Barbara, CA 93106
United States

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