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Other literature type . 2025
License: CC BY NC
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Heterogeneity in Students’ Learning Rates: Evidence from a Brazilian Essay-Writing EdTech Platform

Authors: Barnard González, Cristina Estefanía;

Heterogeneity in Students’ Learning Rates: Evidence from a Brazilian Essay-Writing EdTech Platform

Abstract

Understanding learning differences is crucial for education; however, quantitative evidence describing learning rate patterns is scarce and faces unaddressed biases. This paper examines the variability in Brazilian students’ individual learning rate as they work to improve their argumentative essay writing skills for a high-stakes national assessment to access tertiary education. 12th-grade students engage with a personalized learning platform, providing them with multiple practice opportunities to submit essays and receive personalized feedback. I estimate individual learning rates using multilevel mixed-effects methods and analyze the estimates for both total writing scores and the separate components of the essay writing domain. This study contributes to the learning differences literature by offering novel quantitative evidence on individual learning rates heterogeneity in open writing tasks. The findings support the importance of individualized educational solutions to reduce learning gaps by optimizing the pace of deliberate practice opportunities offered to the students.

Keywords

EdTech, Stanford Graduate School of Education International Education Policy Analysis, learning rates, essay writing, personalized learning, mastery-based learning, Brazil

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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