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Neural Computing and Applications

, Volume 31, Supplement 1, pp 671–681 | Cite as

A hybrid AHP-GA method for metadata-based learning object evaluation

  • Murat İnceEmail author
  • Tuncay Yiğit
  • Ali Hakan Işık
Original Article
  • 275 Downloads

Abstract

A wide variety of demand in e-learning and web-based learning caused a new approach in e-content presentation. In order to accomplish these demands, learning object repositories (LORs) were developed. LORs have many learning objects (LOs) that are used to produce different types of e-content. When there are many LOs in LORs, the evaluation and selection of them become a subjective and time-consuming process. Thus, selecting the most suitable and best qualified LO is considered as a multi-criteria decision-making (MCDM) problem. In this study, a hybrid analytic hierarchy process genetic algorithm (AHP-GA) method was developed for the evaluation of LOs from web-based Intelligent Learning Object Framework (Zonesa) LOR. This proposed hybrid system was used in a real case study and the results demonstrated that the proposed system can be used effectively by both users and machines to produce content by the help of LO metadata.

Keywords

Analytic hierarchy process Learning object selection Metadata Repository Genetic algorithm Recommendation system 

Notes

Acknowledgements

The authors wish to thank the Scientific and Technological Research Council of Turkey (TUBITAK) that supported this project financially with project number EEEAG 115E600.

Compliance with ethical standards

This study was funded by Scientific and Technological Research Council of Turkey (TUBITAK) (grant number EEEAG 115E600).

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© The Natural Computing Applications Forum 2017

Authors and Affiliations

  1. 1.Vocational School of Technical SciencesUniversity of Suleyman DemirelIspartaTurkey
  2. 2.Department of Computer EngineeringUniversity of Suleyman DemirelIspartaTurkey
  3. 3.Department of Computer EngineeringUniversity of Mehmet Akif ErsoyBurdurTurkey

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