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Understanding Mobile Learning Acceptance among University Students with Special Needs: An Exploration through the Lens of Self-Determination Theory

Authors :
Ferhan Sahin
Gizem Yildiz
Source :
Journal of Computer Assisted Learning. 2024 40(4):1838-1851.
Publication Year :
2024

Abstract

Background: Despite the significant emphasis on self-determination in special education and the crucial role of mobile learning, there is a notable absence of path modelling studies that explore the effect of self-determination on the usage of mobile learning by students with special needs. Objectives: This study sought to investigate the intentions of mobile learning usage among students with special needs by proposing a model rooted in the technology acceptance model, complemented by extraneous constructs from self-determination theory (competence, autonomy and relatedness). Methods: The data of the study was obtained online from 1298 special needs university students with eight different types of disabilities. Data were analysed with descriptive statistics, confirmatory factor analysis, structural equation modelling and bootstrapping. Results and Conclusions: The proposed model explained 78.4% of ease of use, 85.2% of usefulness, and 76.5% of intention. 11 of the 12 hypotheses tested within the scope of the model were supported. All hypotheses examining the impacts of self-determination theory constructs on ease of use, usefulness, and intention were validated (8 hypotheses), with the exception of the autonomy [right arrow] intention relationship. Substantial empirical evidence has been acquired to support the role of the self-determination theory in exploring the intention toward mobile learning among university students with special needs. Concurrently, a robust theoretical framework has been introduced to the field of special education to elucidate the acceptance and utilization of technology by university students with special needs.

Details

Language :
English
ISSN :
0266-4909 and 1365-2729
Volume :
40
Issue :
4
Database :
ERIC
Journal :
Journal of Computer Assisted Learning
Publication Type :
Academic Journal
Accession number :
EJ1431917
Document Type :
Journal Articles<br />Reports - Research
Full Text :
https://doi.org/10.1111/jcal.12986