Please use this identifier to cite or link to this item: http://10.9.150.37:8080/dspace//handle/atmiyauni/2103
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dc.contributor.authorRajdev, Amit-
dc.contributor.authorBhatt, Kaushal-
dc.contributor.authorBhatt, Kinjal-
dc.date.accessioned2024-12-03T14:10:27Z-
dc.date.available2024-12-03T14:10:27Z-
dc.date.issued2024-
dc.identifier.citationRajdev, 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),1-12,2148-2403en_US
dc.identifier.issn2148-2403-
dc.identifier.urihttp://10.9.150.37:8080/dspace//handle/atmiyauni/2103-
dc.description.abstractThe 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.isoenen_US
dc.publisherEducational Administration: Theory and Practiceen_US
dc.subjectm-learningen_US
dc.subjectsustainable use,en_US
dc.subjecttask technology fiten_US
dc.subjectexpectation confirmationen_US
dc.subjecthigher education institutionsen_US
dc.titleAnalysis Of Quality Of Mobile Learning (QML) And Its Sustainable Useen_US
dc.title.alternativeTask Technology Fit & Expectation Confirmation Approachen_US
dc.typeArticleen_US
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