Peer Effects in Computer Assisted Learning: Evidence from a Randomized Experiment

Marcel Fafchamps and Di Mo

No 23195, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We conduct a large scale RCT to investigate peer effects in computer assisted learning (CAL). Identification of peer effects relies on three levels of randomization. It is already known that CAL improves math test scores in Chinese rural schools. We find that paired treatment improves the beneficial effects of treatment for poor performers when they are paired with high performers. We test whether CAL treatment reduces the dispersion in math scores relative to controls, and we find statistically significant evidence that it does. We also demonstrate that the beneficial effects of CAL could potentially be strengthened, both in terms of average effect and in terms of reduced dispersion, if weak students are systematically paired with strong students during treatment. To our knowledge, this is the first time that a school intervention has been identified in which peer effects unambiguously help weak students catch up with the rest of the class without imposing any learning cost on other students.

JEL-codes: I24 I25 O15 (search for similar items in EconPapers)
Date: 2017-02
New Economics Papers: this item is included in nep-edu, nep-exp, nep-net and nep-ure
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Published as Marcel Fafchamps & Di Mo, 2018. "Peer effects in computer assisted learning: evidence from a randomized experiment," Experimental Economics, vol 21(2), pages 355-382.

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Journal Article: Peer effects in computer assisted learning: evidence from a randomized experiment (2018)
Working Paper: Peer Effects in Computer Assisted Learning: Evidence from a Randomized Experiment (2015)
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