Are Artificially Intelligent Conversational Chatbots Uniformly Effective in Reducing Summer Melt? Evidence from a Randomized Controlled Trial
| Autor: | Carol Cutler White, Hunter Gehlbach, Lindsay C. Page, Aizat Nurshatayeva |
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| Rok vydání: | 2021 |
| Předmět: |
Medical education
Matriculation Higher education business.industry 05 social sciences 050301 education computer.software_genre Chatbot Education law.invention Outreach Randomized controlled trial law Loan 0502 economics and business College enrollment 050207 economics Computer-mediated communication Psychology business 0503 education computer |
| Zdroj: | Research in Higher Education. 62:392-402 |
| ISSN: | 1573-188X 0361-0365 |
| DOI: | 10.1007/s11162-021-09633-z |
| Popis: | Our field experiment extends prior work on college matriculation by testing the extent to which an artificially intelligent (AI) chatbot’s outreach and support to college students (N = 4442) reduced summer melt and improved first-year college enrollment at a 4-year university. Specifically, we investigate which students the intervention proves most effective for. We find that the AI chatbot increased overall success with navigating financial aid processes, such that student take up of educational loans increased by four percentage points. This financial aid effect was concentrated among would-be first-generation college goers, for whom loan acceptances increased by eight percentage points. In addition, the outreach increased first-generation students’ success with course registration and fall semester enrollment each by three percentage points. Our findings suggest that proactive chatbot outreach to students is likely to be most successful in reducing summer melt among those who may need the chatbot support the most. |
| Databáze: | OpenAIRE |
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