Cited by 36Mobile Learning in EducationInnovative Teaching and Learning MethodsIntelligent Tutoring Systems and Adaptive Learning

Boosting self-regulated learning with mobile interventions: Planning and prompting help children maintain a regular study routine

Breitwieser, Jasmin, Nobbe, Lea, Biedermann, Daniel, Brod, Garvin·2023·Computers & Education

Integrity signals

Registry

Crossref · 10.1016/j.compedu.2023.104879

Cites

21 of 21 references verified0 citation errors · 0 not checkable

Statistics

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

Claims the paper makes

We couldn’t retrieve this paper’s full text, 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?

  • Research on frequent plan reminders suggests that children may benefit from support in maintaining and recalling their implementation intentions over time.

    “Furthermore, research on frequent plan reminders suggests that children may benefit from support in maintaining and recalling their implementation intentions over time (Breitwieser et al., 2023).”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Breitwieser, J., Nobbe, L., Biedermann, D., & Brod, G.
Affiliations
  • Individual Development and Adaptive Education (DE)
  • Goethe University Frankfurt (DE)
Corresponding author
Breitwieser, Jasmin
Venue
Computers & Education
Publisher
Elsevier BV
Published
2023-11
Volume
205
Pages
104879
ISSN
0360-1315 (ISSN-L)
OpenAlex
W4385287532
Cited by
36
References
21
Citations by year
2026: 8 · 2025: 11 · 2024: 14 · 2023: 3
FWCI
6.51
Type
journal article
Language
en
Open access
closed
Locations
Computers & Education (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
  • Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Keywords
student self-regulation, mobile-based interventions, study routines, vocabulary acquisition, planning, prompting, distributed practice, children, study behavior, mobile learning apps

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