Evidence map›Paper›PMID 39271697›Full record

ArticleNPJ science of learning2024

Grit and academic resilience during the COVID-19 pandemic.

Daniel L Chen, Seda Ertac, Theodoros Evgeniou, Xin Miao, Ali Nadaf, Emrah Yilmaz

Abstract read
In one paragraph

Article in NPJ science of learning, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Daniel L ChenToulouse School of Economics, Institute for Advanced Studies, 21 allée de Brienne, 31015 Toulouse cedex 6, Toulouse, France. daniel.li.chen@gmail.com.
Seda ErtacKoc University Department of Economics, Sariyer, Istanbul, 34450, Turkey.
Theodoros EvgeniouTechnology Management and Decision Sciences, INSEAD, 77300, Fontainebleau, France.ORCID http://orcid.org/0000-0001-9525-6110
Xin MiaoAlef Education Building 2, TwoFour54, P.O. Box 769719, Abu Dhabi, UAE.
Ali NadafAlef Education Building 2, TwoFour54, P.O. Box 769719, Abu Dhabi, UAE.
Emrah YilmazKoc University Department of Economics, Sariyer, Istanbul, 34450, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Grit, a non-cognitive skill that indicates perseverance and passion for long-term goals, has been shown to predict academic achievement. This paper provides evidence that grit also predicts student outcomes during the challenging period of the Covid-19 pandemic. We use a unique dataset from a digital learning platform in the United Arab Emirates to construct a behavioral measure of grit. We find that controlling for baseline achievement, students who were grittier according to this measure before the pandemic, register lower declines in math and science scores during the coronavirus period. Using machine learning, behavioral data obtained from the platform prior to the pandemic can explain 77% of the variance in academic resilience. A survey measure of grit coming from the same students, on the other hand, does not have significant predictive power over performance changes. Our findings have implications for interventions on non-cognitive skills, as well as how data from digital learning platforms can be used to predict student behavior and outcomes, which we expect will be increasingly relevant as AI-based learning technologies become more common.

Identifiers

PMID39271697
PMCPMC11399126

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.