Evidence map›Paper›PMID 38626101›Full record

ArticlePloS one2024

Neurodiversity and cognitive load in online learning: A focus group study.

Anne-Laure Le Cunff, Vincent Giampietro, Eleanor Dommett

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
8.6field-weighted citation impact, top 2% of its field
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

4 citing papers in PubMed, 21 citations in OpenAlex.

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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 at 1 institution in 1 country.

Anne-Laure Le CunffDepartment of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.ORCID 0000-0002-6025-1712
Vincent GiampietroDepartment of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
Eleanor DommettDepartment of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
King's College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is widely accepted that cognitive load plays a crucial role in online learning. However, despite neurodevelopmental conditions being the largest category of qualifying disabilities in education, and the rise of online learning, there is little understanding of the factors impacting cognitive load in online learning for neurodivergent students and how these factors differ from those affecting neurotypical students. This study used qualitative comparison groups with neurotypical and neurodivergent students to examine their experiences of cognitive load in online learning. A sample of 26 university students (14 neurotypical and 12 neurodivergent) participated in focus group discussions. While neurodivergent students reported many similar experiences of cognitive load in online learning compared to their neurotypical peers-such as confusion in navigating the content and technical issues-some difficulties were more present for neurodivergent students-such as transcripts including mistakes and inaccessible content presentation-creating additional barriers in effectively engaging with the educational content. The results suggest that neurotypical and neurodivergent students experience similar challenges, albeit to differing degrees of intensity, and that more research is needed to explore the relationship between neurodiversity and cognitive load in online learning.

Indexed as

Education, DistanceCognitionFocus GroupsHumansPeer GroupStudents

Identifiers

PMID38626101
PMCPMC11020716
OpenAlexW4394841284

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.