Cited by 240Artificial Intelligence in EducationEducational Technology and PedagogyArtificial Intelligence in Healthcare and Education

A review on application of artificial intelligence in teaching and learning in educational contexts

Open access
Fahimirad, Mehrnaz, Kotamjani, Sedigheh Shakib·2018·International Journal of Learning and Development

Abstract

Innovative educational technologies have revolutionized the methods of teaching and learning. Recently, with advancements of artificial intelligence, higher education has begun to adopt new technologies. This conceptual review paper aims to investigate the emergence of using artificial intelligence in teaching and learning in education. It examines the educational consequences of emergent technologies on how institutions teach and the way students learn. This study intends to predict the role of artificial intelligence in the future nature of education in a world. The effective application of artificial intelligence methods is considered as a means of improving the quality of teaching and learning. However, the challenges of integrating artificial intelligence in educational institutions is addressed. Moreover, the challenges faced by students in adopting artificial intelligence in terms of students’ support, teaching, learning, and administration are discussed. This paper presents a concise overview of the most recent studies to showcase the application of artificial intelligence in educational contexts. The implications and directions for further research are suggested.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.5296/ijld.v8i4.14057

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

1 of the 28 references couldn’t be matched to a known paper.

Research works printed but not linked: 4

  1. Bengio, Y., Courville, A., Vincent, P., Seliya, N., Wald, R., Muharemagic, E., … Mu, J. (2013). Representation Learning: A Review and New Perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/TPAMI.2013. · DOI
  2. Billings, M. E., Lazarus, M. E., Wenrich, M., Curtis, J. R., & Engelberg, R. A. (2011). The Effect of the Hidden Curriculum on Resident Burnout and Cynicism. Journal of Graduate Medical Education. https://doi.org/10.4300/JGME-D-11-00044. · DOI
  3. Popenici, S. (2013). Higher Education and Affluenza. Popenici. Programas de las Naciones Unidas para el Desarrollo. (2015). Human Development Report 2015. Work for Human Development. Undp. https://doi.org/ISBN: 978-92-1-126398-5
  4. Siân Bayne and Jen Ross. (2016). Manifesto Redux: making a teaching philosophy from networked learning research. Proceedings of the 10 Th International Conference on

Cited by

Sorted by citations

Authors
Fahimirad, M., & Kotamjani, S. S.
Affiliations
  • Taylor's University (MY)
  • University of Technology and Applied Sciences - Shinas (OM)
Corresponding author
Kotamjani, Sedigheh Shakib
Venue
International Journal of Learning and Development
Published
2018-12-15
Volume
8
Issue
4
Pages
106
ISSN
2164-4063 (ISSN-L)
OpenAlex
W2905173347
Cited by
240
References
28
Citations by year
2026: 26 · 2025: 60 · 2024: 71 · 2023: 40 · 2022: 24 · 2021: 13 · 2020: 6
FWCI
7.64
Type
journal article
Language
en
Open access
Locations
  • International Journal of Learning and Development (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Educational Technology and Pedagogy
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
artificial intelligence in education, educational technology, teaching-learning process, higher education, teaching quality, AI implementation challenges, student support, future of education

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