Of the approximately 2.5 million U.S. students who enroll at colleges each year, 48 percent fail to earn a degree within six years. Students who drop out come disproportionately from underserved communities. The societal impact is staggering, costing the U.S. an estimated $4.5 billion in lost earnings and taxes annually. AdmitHub has designed an innovative solution — an artificial intelligence virtual assistant. With it, students receive 24/7 personalized support, and more data is available for universities to provide greater individual support.
AdmitHub, an edtech startup that’s creating conversational artificial intelligence (AI) to guide students to and through college, is trying to make that happen. (In fact, the conversation above was one that we had with the company’s chatbot, Oli.) Today, the Boston-based company announced it has raised $2.2 million in seed funding to develop Oli and other campus-specific chatbots, grow its team, and expand the service to more U.S. and international institutions.
Co-led by Relay Ventures and Reach Capital, with participation from University Ventures and others, the funding round follows a previous $800,000 that the company pulled after participating in 2015 Techstars accelerator program. Combined, AdmitHub has raised a total $2.95 million in seed funding
Deep reinforcement learning using convolutional neural networks is the technology behind autonomous vehicles. Could this same technology facilitate the road to college? During the summer between high school and college, college-related tasks that students must navigate can hinder successful 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 implemented and tested this system through a field experiment with Georgia State University (GSU). GSU-committed students assigned to treatment exhibited greater success with pre-enrollment requirements and were 3.3 percentage points more likely to enroll on-time. Enrollment impacts are comparable to those in prior interventions but with substantially reduced burden on university staff. Given the capacity for AI to learn over time, this intervention has promise for scaling personalized college transition guidance.