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Analysis Of Quality Of Mobile Learning (QML) And Its Sustainable Use

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dc.contributor.author Rajdev, Amit
dc.contributor.author Bhatt, Kaushal
dc.contributor.author Bhatt, Kinjal
dc.date.accessioned 2024-12-03T14:10:27Z
dc.date.available 2024-12-03T14:10:27Z
dc.date.issued 2024
dc.identifier.citation Rajdev, Amit; Bhatt, Kaushal;Bhatt, Kinjal (2024), Analysis Of Quality Of Mobile Learning (QML) And Its Sustainable Use: Task Technology Fit & Expectation Confirmation Approach, Educational Administration: Theory and Practice,30(4),1-12,2148-2403 en_US
dc.identifier.issn 2148-2403
dc.identifier.uri http://10.9.150.37:8080/dspace//handle/atmiyauni/2103
dc.description.abstract The purpose of the study was to analyze the quality of mobile learning from the perspective of the students studying in higher educational institutions. The sustainable use of mobile learning and satisfaction of students were analyzed using task-technology fit, expectation-confirmation model and input output model. The study was confirmatory in nature and cross-sectional research design was used. 321 students were selected using convenience sampling method from seven different higher educational institutions of Gujarat (India). The structured questionnaire was used to collect the data. Two multiple linear regression models were used to identify the predictors of satisfaction and sustainable use of mobile learning. SPSS was used to analyze the data. The results indicate that satisfaction of the students from mobile learning is more influenced by process part while sustainable use of mobile learning is influenced by resource part of mobile learning. en_US
dc.language.iso en en_US
dc.publisher Educational Administration: Theory and Practice en_US
dc.subject m-learning en_US
dc.subject sustainable use, en_US
dc.subject task technology fit en_US
dc.subject expectation confirmation en_US
dc.subject higher education institutions en_US
dc.title Analysis Of Quality Of Mobile Learning (QML) And Its Sustainable Use en_US
dc.title.alternative Task Technology Fit & Expectation Confirmation Approach en_US
dc.type Article en_US


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