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A model for sustainable mobile education beyond the Covid-19 pandemic

Datos Bibliográficos

ID22166124
AutoresAhmed Abdulhameed Al Mulhem, Ahmed Al Mulhem (0000-0002-0093-5012, King Faisal University, autor de correspondencia)
Año2025
Volumen10
Fecha de publicación2025-11-25
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Education (JOURNAL)
Identificadores de la revistaISSN: 2504-284X • E-ISSN: 2504-284X
EditorialFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/feduc.2025.1657635
OpenAlexW4416676684
IdiomaEN
Referencias citadas66

Mobile learning (ML) was widely adopted during the coronavirus disease 2019 (COVID-19) pandemic, but its sustained use post-pandemic is not guaranteed. This study identifies the factors influencing university students’ intention to continue using ML. Using the Unified Theory of Acceptance and Use of Technology (UTAUT-2) model, data from 445 students at King Faisal University were analyzed via structural equation modeling. The results showed that attitude toward ML was significantly influenced by effort expectancy ( β = 0.620, p < 0.001), performance expectancy ( β = 0.521, p < 0.001), and hedonic motivation ( β = 0.313, p < 0.001). For continuous intention, habit was the strongest predictor ( β = 0.445, p < 0.001), followed by hedonic motivation ( β = 0.471, p < 0.001) and attitude ( β = 0.175, p < 0.05). Performance expectancy, effort expectancy, social influence, and facilitating conditions had no significant direct effects on continuance intention. These findings confirm habit as the cornerstone of post-pandemic ML continuance, highlighting a shift from utilitarian factors to automated use and enjoyment. Post-pandemic ML integration must strategically foster habitual use and enhance enjoyment, moving beyond utility-focused approaches. This study provides evidence-based insights for educational leaders and platform developers to guide ML’s sustainable integration

Continuance · Cornerstone · Expectancy theory · Habit · Life expectancy · Pandemic · Structural equation modeling · Unified theory of acceptance and use of technology · Impact of Technology on Adolescents · Mobile Learning in Education · Technology Adoption and User Behaviour

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