CoChat
Sign Up
Cited by 4Education Methods and TechnologiesEducational Technology and E-LearningEducational Technology in Learning

Pedagogy, Didactics and Educational Technologies: Research Experiences and Outcomes in Enhanced Learning and Teaching at Cadi Ayyad University

·2022·Lecture Notes in Educational Technology
DOI 10.1007/978-981-19-5137-4
Open this paper in CoChat — free account

Integrity signals

Registry

Crossref · 10.1007/978-981-19-5137-4

Cites

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?

  • In [37], machine learning within the LearnFit framework was used to personalize and adapt learning paths using learning style models and learner profiles.

    “Machine learning is used in this article to apply machine learning techniques within the LearnFit framework to personalize and adapt the learning paths for learners.”

    From Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review (2023) · cites this paper as [37]

Cited by

Sorted by citations

Related

Venue
Lecture Notes in Educational Technology
Publisher
Springer Nature Singapore
Published
2022
ISSN
  • 2196-4963 (ISSN-L)
  • 2196-4971
DOI
10.1007/978-981-19-5137-4
OpenAlex
W4294433380
Cited by
4
References
0
Citations by year
2026: 1 · 2024: 1 · 2023: 2
FWCI
2.17
Type
book
Language
en
Open access
closed
Licence
Locations
Lecture notes in educational technology (publishedVersion)
Topics
  • Social Sciences › Education › Education Methods and Technologies
  • Physical Sciences › Computer Science › Information Systems › Educational Technology and E-Learning
  • Physical Sciences › Computer Science › Information Systems › Educational Technology in Learning
Keywords
pedagogy, didactics, educational technology, university teaching

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