Cited by 275Impact of Technology on AdolescentsPersonal Information Management and User BehaviorMobile Learning in Education

The effect of cellphones on attention and learning: The influences of time, distraction, and nomophobia

Mendoza, Jessica S., Pody, Benjamin C., Lee, Seungyeon, Kim, Minsung, McDonough, Ian M.·2018·Computers in Human Behavior

Abstract

Abstract Excessive cellphone use impacts attention and learning in classrooms. Given that attention declines over time, we investigated when during lecture cellphones might impair learning. Across two experiments, participants watched a 20-min lecture under different cellphone conditions (keep or remove). Groups who kept their cellphones received distracting text messages during the lecture. Participants were quizzed on the lecture. Quiz questions were divided into four segments depending on when the material was presented. Lastly, participants' nomophobia—the fear of being without access to one's cellphone—was assessed. Participants who kept their cellphone performed worse on the quiz for material presented in the 3rd quarter of the lecture than those without cellphones. Distracted participants performed worse on the test for the same material than those who were not distracted. Participants higher in nomophobia, especially on subscales having to do with losing connectedness and giving up convenience, performed worse on the quiz for material that occurred in the 3rd quarter of the lecture. Findings indicate that having cellphones in a short lecture has its largest impact on attention and learning 10–15 min into the lecture. This study provides novel insights into the interactions between technology and learning to help educators and students optimize learning.

Integrity signals

Registry

Crossref · 10.1016/j.chb.2018.04.027

Cites

62 of 62 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The effect of smartphone presence/availability during cognitive performance is moderated by mobile phone dependence, Internet use/attachment, and nomophobia.

    “Recent research also suggests that the effect of smartphone presence/availability during cognitive performance is moderated by mobile phone (psychological) dependence21, Internet use/attachment30, and nomophobia (i.e., the fear of being without access to one’s cell phone16), all of these constructs being assessed with self-report scales.”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Mendoza, J. S., Pody, B. C., Lee, S., Kim, M., & McDonough, I. M.
Affiliations
  • University of Alabama (US)
  • University of Arkansas at Monticello (US)
  • University of Nebraska–Lincoln (US)
Corresponding author
McDonough, Ian M.
Venue
Computers in Human Behavior
Publisher
Elsevier BV
Published
2018-09
Volume
86
Pages
52-60
ISSN
0747-5632 (ISSN-L)
OpenAlex
W2797796630
Cited by
275
References
60
Citations by year
2026: 17 · 2025: 36 · 2024: 37 · 2023: 41 · 2022: 46 · 2021: 36 · 2020: 39 · 2019: 19 · 2018: 4
FWCI
55.67
Type
journal article
Language
en
Open access
closed
Locations
Computers in Human Behavior (publishedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
  • Social Sciences › Decision Sciences › Information Systems and Management › Personal Information Management and User Behavior
  • Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
Keywords
mobile devices, attention, learning, nomophobia, distraction, text messages, lectures, time of day effects, technology and learning, classroom technology use

About these checks

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.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review