Humans versus Chatbots: Scaling-up Behavioral Interventions to Reduce Teacher Shortages

Nicolas Ajzenman (), Gregory Elacqua (), Analía Jaimovich () and Graciela Pérez-Núñez ()
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Nicolas Ajzenman: McGill University
Gregory Elacqua: Inter-American Development Bank
Analía Jaimovich: Inter-American Development Bank
Graciela Pérez-Núñez: Inter-American Development Bank

No 16404, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Empirical results in economics often stem from success in controlled experimental settings, but often fail when scaled up. This study presents a behavioral intervention and a scalable equivalent aimed at reducing teacher shortages by motivating high school students to pursue an education degree. The intervention was delivered through WhatsApp chats by trained human promoters (humans arm) and rule-based Chatbots programmed to closely replicate the humans program (bots arm). Results show that the humans arm successfully increased high-school students' demand for and enrollment in education majors, particularly among high-performing students. The bots arm showed positive but smaller and statistically insignificant effects. These findings indicate that a relatively low-cost intervention can effectively reduce teacher shortages, but scaling up such interventions may have limitations. Therefore, testing scalable solutions during the design stage of experiments is crucial.

Keywords: teachers; teacher policy; teacher shortages; scale-up; behavioral; bots (search for similar items in EconPapers)
JEL-codes: D91 I23 I25 (search for similar items in EconPapers)
Pages: 47 pages
Date: 2023-08
New Economics Papers: this item is included in nep-exp and nep-ure
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