doi: 10.18178/ijiet.2017.7.12.989
AHP-TOPSIS Method for Learning Object Metadata Evaluation
M. İnce1
,
T. Yiğit2 ,
A. H. Işık3
- 1Vocational School of Technical Sciences, University of Suleyman Demirel, Isparta, 32200, Turkey
- 2Computer Engineering Department, University of Suleyman Demirel, Isparta, 32200, Turkey
- 3Computer Engineering Department, University of Mehmet Akif Ersoy, Burdur, 15030, Turkey
Abstract
Increasing usage of computers in educational systems such as web based learning systems cause huge e-content needs. In this context, Learning Objects (LOs), stored in Learning Object Repositories (LORs), are used to produce e-content and other educational materials. Evaluation and selection of LOs are difficult and time consuming process when LO and their descriptive metadata numbers are high. Therefore, LO selection process is considered as a multi criteria decision making (MCDM) problem. In this study, analytic hierarchy process - technique for order of preference by similarity to ideal solution (AHP-TOPSIS) methods are combined for selection of LOs from web-based Intelligent Learning Object Framework LOR that is called ZONESA. The results of the system, used in a real case study, showed that the proposed system can be used effectively to produce appropriate content using LO metadata.
Keywords
- Analytic hierarchy process
- learning object selection
- metadata
- topsis
How to Cite
M. İnce, T. Yiğit, and A. H. Işık, "AHP-TOPSIS Method for Learning Object Metadata Evaluation," International Journal of Information and Education Technology, vol. 7, no. 12, pp. 884-887, 2017. https://doi.org/10.18178/ijiet.2017.7.12.989
Copyright & License
Copyright © 2017 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).