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An Adaptive software architectural framework for an interactive learning toolkit

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dc.contributor.advisor Meedeniya D
dc.contributor.author Jayasiriwardene DPS
dc.date.accessioned 2023
dc.date.available 2023
dc.date.issued 2023
dc.identifier.citation Jayasiriwardene, D,P,S. (2023). An Adaptive software architectural framework for an interactive learning toolkit [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/22104
dc.identifier.uri http://dl.lib.uom.lk/handle/123/22104
dc.description.abstract At present, a significant demand has emerged for online education tools that can used as a replacement for classroom education. Due to the ease of access and the highavailability of mobile devices, the preference of many users is focused on m-learningapplications. Thus, this study presents an adaptive software architectural framewfor an interactive learning toolkit. As a case study, the application is applied toprimary education sector in Sri Lanka, as there is a lack of learning tools that allteachers and students to interact effectively. Accordingly, a software architecturaframework was designed with the features of adaptivity, learning content authoring, learning content management, low resource utilization, and low power consumptiThe study includes an extensive literature review conducted to identify unique gapsexisting studies. Further, the study designs and develops an architecture with intended feature effectively embedded in it. Furthermore, an m-learning applicanamed “iLearn” is developed as a proof-of-concept by implementing the architecturdesign. Moreover, the prototype was evaluated for functional requirements successfully conducting unit tests and user interface tests. The non-functionarequirements of the application were evaluated by conducting a system usabilsurvey for 20 teachers and 20 students, which received a good usability score of 80.5%and 83.6%, respectively. Also, the performance of the application was tested received a good overall outlook on performance where it was found that the applicahas a below-average consumption of memory, CPU, and battery at peak performancThe application is concluded as a success, with the potential to enhance with cuttingedge technology. en_US
dc.language.iso en en_US
dc.subject ADAPTIVE LEARNING en_US
dc.subject LEARNING CONTENT AUTHORING en_US
dc.subject INTERACTIVE LEARNING en_US
dc.subject PERSONALIZED LEARNING en_US
dc.subject M-LEARNING en_US
dc.subject COMPETENCY-BASED ADAPTIVITY en_US
dc.subject COMPUTER SCIENCE AND ENGINEERING-Dissertations en_US
dc.subject COMPUTER SCIENCE-Dissertations en_US
dc.title An Adaptive software architectural framework for an interactive learning toolkit en_US
dc.type Thesis-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.degree MSc In Computer Science and Engineering by Research en_US
dc.identifier.department Department of Computer Science and Engineering en_US
dc.date.accept 2023
dc.identifier.accno TH5144 en_US


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