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Web-based learning object selection software using analytical hierarchy process

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dc.creator YİĞİT, Tuncay
dc.creator Isik, Ali Hakan
dc.creator Ince, Murat
dc.date 2014-07-31T21:00:00Z
dc.date.accessioned 2020-10-06T10:48:53Z
dc.date.available 2020-10-06T10:48:53Z
dc.identifier 927d78f6-1f0e-4931-8ade-87243626dee7
dc.identifier 10.1049/iet-sen.2013.0116
dc.identifier https://avesis.sdu.edu.tr/publication/details/927d78f6-1f0e-4931-8ade-87243626dee7/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/66510
dc.description The concepts of sustainability and reusability have great importance in engineering education. In this context, metadata provides reusability and the effective use of Learning Objects (LOs). In addition, searching the huge LO Repository with metadata requires too much time. If the selection criteria do not exactly match the metadata values, it is not possible to find the most appropriate LO. When this situation arises, the multi-criteria decision making (MCDM) method can meet the requirements. In this study, the SDUNESA software was developed and this software allows for the selection of a suitable LO from the repository by using an analytical hierarchy process MCDM method. This web-based SDUNESA software is also used to store, share and select a suitable LO in the repository. To meet these features, the SDUNESA software contains Web 2.0 technologies such as AJAX, XML and SOA Web Services. The SDUNESA software was especially developed for computer engineering education. Instructors can use this software to select LOs with defined criteria. The parameters of the web-based SDUNESA learning object selection software that use the AHP method are defined under the computer education priorities. The obtained results show that the AHP method selects the most reliable learning object that meets the criteria.
dc.language eng
dc.rights info:eu-repo/semantics/closedAccess
dc.title Web-based learning object selection software using analytical hierarchy process
dc.type info:eu-repo/semantics/article


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