Neurodiversity Positively Predicts Perceived Extraneous Load in Online Learning

A Quantitative Research Study

Bibliographic Data

ID22047762
AuthorsAnne-Laure Le Cunff (0000-0002-6025-1712, King's College London, corresponding author), Vincent Giampietro (0000-0002-9381-8201, King's College London), Eleanor J Dommett (0000-0002-6973-8762, King's College London)
Year2024
Volume14
Issue5
Pages516
Publication date2024-05-10
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEducation Sciences (JOURNAL)
Journal identifiersISSN: 2227-7102 • E-ISSN: 2227-7102
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/educsci14050516
OpenAlexW4396890692
LanguageEN
Citations received4
References cited83

Working memory impairments are common in neurodevelopmental conditions, potentially impacting how neurodivergent students experience cognitive load during learning. We conducted a survey with 231 participants focused on students with attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and dyslexia. Parametric tests and a regression analysis were used to investigate the relationship between neurodiversity and perceived cognitive load in online learning. Neurodivergent students reported significantly higher extraneous cognitive load (ECL) in online learning compared to their neurotypical peers. However, no significant differences in perceived intrinsic and germane cognitive load were found between the two groups. Neurodiversity, and specifically ADHD, positively predicted perceived ECL in online learning. This study provides novel insights into the association between neurodiversity and cognitive load in online learning, suggesting a need for targeted support to help neurodivergent students reduce ECL in online learning environments and highlighting the importance of promoting inclusive educational practices that meet the needs of all students

Cognitive psychology · Computer Science · Educational Games and Gamification · Online Learning and Analytics · Psychology · Social Psychology · Visual and Cognitive Learning Processes

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