PreprintCited by 3Impact of Technology on AdolescentsSchool Choice and PerformanceMobile Learning in Education

Removing Phones from Classrooms Improves Academic Performance

Open access
Sungu, Alp, Choudhury, Pradeep Kumar, Bjerre-Nielsen, Andreas·2025·SSRN Electronic Journal

Integrity signals

Registry

Crossref · 10.2139/ssrn.5370727

Cites

16 of 16 references verified0 citation errors · 0 not checkable

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  • Sungu, Choudhury and Bjerre-Nielsen (2025) found that mandatory in-class phone collection in Indian higher education settings improved grades, with no significant changes in overall student well-being.

    “Sungu, Choudhury and Bjerre-Nielsen (2025) find that mandatory in-class phone collection in Indian higher education settings improved grades, with no significant changes in overall student well-being.”

    From The Effects of School Phone Bans: National Evidence from Lockable Pouches (2026) · cites this paper as Sungu, Choudhury and Bjerre-Nielsen (2025)

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Authors
Sungu, A., Choudhury, P. K., & Bjerre-Nielsen, A.
Affiliations
  • University of Pennsylvania (US)
  • Jawaharlal Nehru University (IN)
  • University of Copenhagen (DK)
Corresponding author
Sungu, Alp
Venue
SSRN Electronic Journal
Publisher
Elsevier BV
Published
2025
ISSN
1556-5068 (ISSN-L)
OpenAlex
W4413194261
Cited by
1
References
16
Citations by year
2025: 1
Type
posted content
Language
en
Open access
Locations
SSRN Electronic Journal (acceptedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
  • Social Sciences › Education › School Choice and Performance
  • Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
Keywords
academic performance, student grades, fear of missing out, student distraction, student well-being, academic motivation, online harassment, student engagement, lower-performing students

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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