Diminishing Marginal Returns to Computer-Assisted Learning
The previous expansion of EdTech as a substitute for traditional learning around the world, the recent full-scale substitution due to COVID-19, and potential future shifts to blended approaches suggest that it is imperative to understand input substitutability between in-person and online learning. We explore input substitutability in education by employing a novel randomized controlled trial that varies dosage of computer-assisted learning (CAL) as a substitute for traditional learning through homework. Moving from zero to a low level of CAL, we find positive substitutability of CAL for traditional learning. Moving from a lower to a higher level of CAL, substitutability changes and is either neutral or even negative. The estimates suggest that a blended approach of CAL and traditional learning is optimal. The findings have direct implications for the rapidly expanding use of educational technology worldwide prior to, during and after the pandemic.
Eric Bettinger & Robert Fairlie & Anastasia Kapuza & Elena Kardanova & Prashant Loyalka & Andrey Zakharov, 2023. "Diminishing Marginal Returns to Computer‐Assisted Learning," Journal of Policy Analysis and Management, vol 42(2), pages 552-570. citation courtesy of