Toh, Shee Ying (2016) Ontology for mobile device utilization: towards knowledge personalization in mobile learning. Masters thesis, Universiti Teknologi Malaysia, Faculty of Computing.
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Abstract
Mobile devices usage has grown significantly in the last decade. With the advent of mobile technology, mobile devices have transformed people lifestyle including learning style. Mobile learning uses mobile technologies to carry out learning process. Typically, mobile learning involved individual learning with less or without teacher‟s supervision and guidance. This means that the learners need to manage their knowledge on their own. However, not all learners have similar learning ability and behaviour. The ways they manage their knowledge are different. In this study, an ontology for mobile device utilization is proposed to study the behaviour of learners in the usage of mobile device. Then, potential personalization feature, that can be included in mobile learning, can be identified based on the mobile device utilization of learners. The ways they use their mobile device is studied to identify the potential personalization feature they will use to manage their knowledge. Knowledge personalization in mobile learning is analysed based on the ontology of mobile device utilization where knowledge personalization is the ability to provide knowledge according to the learners‟ behaviours. Motivated by the lack of research on knowledge personalization in mobile learning especially in Malaysia, this study is conducted in Malaysia. Design science research method is used for this study and METHONTOLOGY is used for the development of ontology. The resulted ontology consists of a total of 39 concepts and 3 tiers. Questionnaire is distributed to lower secondary students in Malaysia to collect the data about the mobile device utilization. This questionnaire is mapped with concepts in the ontology developed and the finding is analysed toward knowledge personalization in mobile learning. The result from the questionnaire conducted showed that each concept is reliable and suitable for knowledge personalization in mobile learning.
Item Type: | Thesis (Masters) |
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Additional Information: | Thesis (Sarjana Sains (Teknologi Maklumat - Pengurusan)) - Universiti Teknologi Malaysia, 2016; Supervisor : Dr. Syed Norris Hikmi Syed Abdullah |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Computing |
ID Code: | 78052 |
Deposited By: | Fazli Masari |
Deposited On: | 23 Jul 2018 05:33 |
Last Modified: | 23 Jul 2018 05:33 |
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