Evidence map›Paper›PMID 42664199›Full record

ArticlePloS one2026

These children can become independent thanks to artificial intelligence! - A qualitative analysis of pre‑service teachers' views on the use of artificial intelligence in special education.

Hale Cotuk Yucel, Ali Kaya, Merve Arslan

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hale Cotuk YucelDepartment of Special Education, Nevsehir Haci Bektas Veli University, Nevsehir, Türkiye.ORCID https://orcid.org/0000-0003-4639-9216
Ali KayaDepartment of Special Education, Nevsehir Haci Bektas Veli University, Nevsehir, Türkiye.
Merve ArslanDepartment of Special Education, Nevsehir Haci Bektas Veli University, Nevsehir, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of artificial intelligence (AI) into educational settings has accelerated in recent years, with growing implications for special education. However, the perceptions and evaluations of pre-service special education teachers, who will deliver AI-supported instruction in the near future, remain insufficiently examined.

objectiveThis study aimed to interpret the meanings that prospective special education teachers attribute to the use of AI in special education and to articulate the structures of significance through which those meanings are organized in their accounts.

methodsEmploying an interpretive phenomenological design, we conducted semi-structured individual interviews with 14 pre-service teachers who had previously participated in artificial intelligence-based courses and projects. Content analysis of the data yielded four themes: (a) Teacher, (b) Child and Family, (c) Education, and (d) Artificial Intelligence and Future.

resultsFindings indicate that participants conceptualized AI not merely as a tool perceived to individualize instructional processes, but also as a potential agent perceived to transform pedagogical roles. Participants articulated the view that AI could support critical domains for learners with special needs, such as independent living skills, social interaction, and decision-making, while also questioning risks such as social isolation, data privacy, dependency, and ethical uncertainty.

conclusionThe participants' accounts collectively suggest a need for ethics-driven AI literacy in special education that foregrounds critical thinking and person-centered support.

Indexed as

Artificial IntelligenceEducation, SpecialSchool TeachersAdultChildFemaleHumansMaleQualitative Research

Identifiers

PMID42664199
PMCPMC13524254

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.