Evidence map›Paper›PMID 37134094›Full record

ArticlePloS one2023

Assignment strategies modulate students' academic performance in an online learning environment during the first and second COVID-19 related school closures.

Markus Wolfgang Hermann Spitzer, Korbinian Moeller, Sebastian Musslick

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Markus Wolfgang Hermann SpitzerDepartment of Psychology, University of Basel, Basel, Switzerland.ORCID 0000-0001-6040-1939
Korbinian MoellerCentre for Mathematical Cognition, School of Science, Loughborough University, Loughborough, United Kingdom.
Sebastian MusslickDepartment of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A growing number of studies seek to evaluate the impact of school closures during the ongoing COVID-19 pandemic. While most studies reported severe learning losses in students, some studies found positive effects of school closures on academic performance. However, it is still unclear which factors contribute to the differential effects observed in these studies. In this article, we examine the impact of assignment strategies for problem sets on the academic performance of students (n ≈ 16,000 from grades 4-10 who calculated ≈ 170,000 problem sets) in an online learning environment for mathematics, during the first and second period of pandemic-related school closures in Germany. We observed that, if teachers repeatedly assigned single problem sets (i.e., a small chunk of on average eight mathematical problems) to their class, students' performance increased significantly during both periods of school closures compared to the same periods in the previous year (without school closures). In contrast, our analyses also indicated that, if teachers assigned bundles of problem sets (i.e., large chunks) or when students self-selected problem sets, students' performance did not increase significantly. Moreover, students' performance was generally higher when single problem sets were assigned, compared to the other two assignment types. Taken together, our results imply that teachers' way of assigning problem sets in online learning environments can have a positive effect on students' performance in mathematics.

Indexed as

Academic PerformanceCOVID-19Education, DistanceHumansPandemicsSchoolsStudents

Identifiers

PMID37134094
PMCPMC10155976

What OpenQuestion holds

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LicenceCC BY
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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.