Perceived Usefulness and Satisfaction with Location Adaptive Smart Learning

dc.contributor.authorAlhalabi, Marah
dc.contributor.authorAlblooshi, Taherah
dc.contributor.authorBa'Ba', Leen
dc.contributor.authorSliman, Huda
dc.contributor.authorKhan, Esrat
dc.contributor.authorYaghi, Maha
dc.contributor.authorGhazal, Mohammed
dc.date.accessioned2024-06-02T10:55:38Z
dc.date.available2024-06-02T10:55:38Z
dc.date.issued2022-07
dc.description.abstractTechnology has been increasingly important for current and future societies, becoming even more so as the decades pass. This research work presents an educational application with location adaptive smart mobile learning. The educational tool enhances the knowledge of the society about the monuments and landmarks of the country, enriching the experience of living. An inhabitant needs to enhance their knowledge about the magnificent landmarks available in their vicinity to establish a deep connection with people from that region. Using geofencing technology, we develop a framework that shows pertinent educational data based on the user's current location. The app enables data retrieval and integration using Google scrapers to incorporate the most relevant information from existing web pages. Moreover, we distribute a survey to determine whether the mobile application is beneficial, has pedagogical features, and is satisfactory to the UAE society based on the Technology Acceptance Model factors. After gathering the results, we analyze the alpha coefficient, the outcome of the reliability test. The proposed application achieved a Cronbach's alpha coefficient of 0.874; therefore, the internal consistency is good. The Department of Culture and Tourism can also adopt the smart application to integrate information that educates visitors and tourists. Keywords Geofencing, Location-adaptive, Mobile learning, Perceived usefulness and satisfaction, Technology Acceptance Model (TAM)
dc.identifier.citationAlhalabi, M., Alblooshi, T., Ba’ba, L., Sliman, H., Khan, E., Yaghi, M., & Ghazal, M. (2022, July). Perceived Usefulness and Satisfaction with Location Adaptive Smart Learning. In 2022 2nd International Conference on Computing and Machine Intelligence (ICMI) (pp. 1-5). IEEE.
dc.identifier.doihttps://doi.org/10.1109/ICMI55296.2022.9873746
dc.identifier.urihttps://dspace.adu.ac.ae/handle/1/5551
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.titlePerceived Usefulness and Satisfaction with Location Adaptive Smart Learning
dc.typeConference Paper

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