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Application of Multiple Criteria Decision Analysis and Optimisation Methods in Evaluation of Quality of Learning Objects

Application of Multiple Criteria Decision Analysis and Optimisation Methods in Evaluation of Quality of Learning Objects

Eugenijus Kurilovas, Irina Vinogradova, Silvija Serikoviene
Copyright: © 2013 |Pages: 15
ISBN13: 9781466629493|ISBN10: 1466629495|EISBN13: 9781466629509
DOI: 10.4018/978-1-4666-2949-3.ch010
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MLA

Kurilovas, Eugenijus, et al. "Application of Multiple Criteria Decision Analysis and Optimisation Methods in Evaluation of Quality of Learning Objects." Curriculum, Learning, and Teaching Advancements in Online Education, edited by Mahesh S. Raisinghani, IGI Global, 2013, pp. 136-150. https://doi.org/10.4018/978-1-4666-2949-3.ch010

APA

Kurilovas, E., Vinogradova, I., & Serikoviene, S. (2013). Application of Multiple Criteria Decision Analysis and Optimisation Methods in Evaluation of Quality of Learning Objects. In M. Raisinghani (Ed.), Curriculum, Learning, and Teaching Advancements in Online Education (pp. 136-150). IGI Global. https://doi.org/10.4018/978-1-4666-2949-3.ch010

Chicago

Kurilovas, Eugenijus, Irina Vinogradova, and Silvija Serikoviene. "Application of Multiple Criteria Decision Analysis and Optimisation Methods in Evaluation of Quality of Learning Objects." In Curriculum, Learning, and Teaching Advancements in Online Education, edited by Mahesh S. Raisinghani, 136-150. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2949-3.ch010

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Abstract

This paper analyses and presents the new scientific models and methods for the expert evaluation of quality of learning objects (LOs) paying special attention to LOs reusability level. Currently all existing approaches in the area are quite subjective and depend only on the experience of the decision-makers. The authors analyse several scientific methods and principles to minimise the subjectivity level in the expert evaluation of LOs quality. They are: (a) the principles of multi-criteria decision analysis for identification of quality criteria, (b) technological quality criteria classification principle, (c) fuzzy group decision making theory to obtain evaluation measures, (d) normalisation of the weights of criteria, and (e) scalarisation method for LOs quality optimisation. The authors demonstrate that the complex application of these approaches could significantly improve the quality of the expert evaluation of LOs and noticeably reduce the level of the expert evaluation subjectivity. The paper also presents the example of practical application of these approaches for evaluation of LOs for Mathematics subject.

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