CoChat
Sign Up
Cited by 225Artificial Intelligence in EducationEthics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

The DOI matches its Crossref record; 76 of the 76 references it cites were found in a registry or an index.

Unveiling the shadows: Beyond the hype of AI in education

Open access
Al-Zahrani, Abdulrahman M.·2024·Heliyon
DOI 10.1016/j.heliyon.2024.e30696PMC PMC11087970
Open this paper in CoChat — free account

Abstract

Despite the wave of enthusiasm for the role of Artificial Intelligence (AI) in reshaping education, critical voices urge a more tempered approach. This study investigates the less-discussed 'shadows' of AI implementation in educational settings, focusing on potential negatives that may accompany its integration. Through a multi-phased exploration consisting of content analysis and survey research, the study develops and validates a theoretical model that pinpoints several areas of concern. The initial phase, a systematic literature review, yielded 56 relevant studies from which the model was crafted. The subsequent survey with 260 participants from a Saudi Arabian university aimed to validate the model. Findings confirm concerns about human connection, data privacy and security, algorithmic bias, transparency, critical thinking, access equity, ethical issues, teacher development, reliability, and the consequences of AI-generated content. They also highlight correlations between various AI-associated concerns, suggesting intertwined consequences rather than isolated issues. For instance, enhancements in AI transparency could simultaneously support teacher professional development and foster better student outcomes. Furthermore, the study acknowledges the transformative potential of AI but cautions against its unexamined adoption in education. It advocates for comprehensive strategies to maintain human connections, ensure data privacy and security, mitigate biases, enhance system transparency, foster creativity, reduce access disparities, emphasize ethics, prepare teachers, ensure system reliability, and regulate AI-generated content. Such strategies underscore the need for holistic policymaking to leverage AI's benefits while safeguarding against its disadvantages.

Overview

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 · 10.1016/j.heliyon.2024.e30696

Cites

76 of 76 references verified0 citation errors · 0 not checkable

Statistics

Verification

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.

Citations

Cites

Show all 65 references

Research works printed but not linked: 6

  1. Chaudhry, 2022, vol. 2, 157
  2. Copeland, 2023, Artificial intelligence (AI) | definition, examples, types, applications, companies, & facts, Encyclopedia Britannica
  3. Shneiderman, 2020, vol. 1, 73
  4. Heinrichs, 2021, vol. 37, 143
  5. Owe, 2021, vol. 1, 517
  6. Sit, 2020, vol. 11

Cited by

Sorted by citations

Items 201–225 of 225

Related

See all

Metadata

Authors
Al-Zahrani, A. M.
Affiliations
University of Jeddah (SA)
Corresponding author
Al-Zahrani, Abdulrahman M.
ORCID
Al-Zahrani, Abdulrahman M.
Venue
Heliyon
Publisher
Elsevier BV
Published
2024-05
Volume
10
Issue
9
Pages
e30696
ISSN
2405-8440 (ISSN-L)
DOI
10.1016/j.heliyon.2024.e30696
PMC
PMC11087970
OpenAlex
W4396622564
Cited by
225
References
65
Citations by year
2026: 116 · 2025: 101 · 2024: 8
FWCI
84.60
Type
journal article
Language
en
Open access
Licence
Locations
  • Heliyon (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Social Sciences › Education › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
artificial intelligence in education, AI implementation challenges, data privacy and security, algorithmic bias, AI transparency, critical thinking, equitable access, AI ethics, teacher professional development, AI-generated content, AI reliability

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