نمایش مختصر رکورد

dc.contributor.authorGhannadpour, Seyed Fariden_US
dc.contributor.authorjokar, maryamen_US
dc.contributor.authorMakui, ahmaden_US
dc.date.accessioned1399-07-09T03:59:06Zfa_IR
dc.date.accessioned2020-09-30T03:59:06Z
dc.date.available1399-07-09T03:59:06Zfa_IR
dc.date.available2020-09-30T03:59:06Z
dc.date.issued2018-07-01en_US
dc.date.issued1397-04-10fa_IR
dc.date.submitted2018-04-23en_US
dc.date.submitted1397-02-03fa_IR
dc.identifier.citationGhannadpour, Seyed Farid, jokar, maryam, Makui, ahmad. (2018). Fuzzy analytical network process logic for performance measurement system of e-learning centers of universities. Journal of Industrial and Systems Engineering, 11(3), 261-280.en_US
dc.identifier.issn1735-8272
dc.identifier.urihttp://www.jise.ir/article_68761.html
dc.identifier.urihttps://iranjournals.nlai.ir/handle/123456789/252077
dc.description.abstractThis paper proposes an efficient performance measurement system to evaluate the excellence of e-learning centers of universities. The proposed system uses the analytic network process (ANP) as an effective multi-criteria decision making (MCDM) method and its fuzzy mode to respond to uncertainties in judgements. This system also needs a targeted and systematic criteria set which is collected through comprehensive literature studies and experiences of faculty members.The performance of e-learning centers can then be systemically measured and managed by finding the relationship between these criteria, comparing the pairwise of criteria together and gaining their importance under uncertainty. In this paper, eight main criteria and twenty-five sub criteria is identified by a comprehensive survey on a statistical community consist of faculty members, staff and students of e-learning centers. Based on the results, the criteria for measuring university performance are mainly "student, teacher, educational content, communication, research, scheduling, continuous improvement and infrastructure." From the results of the final weights obtained, the "master's attitude toward the course" is most important in measuring performance. The sub-criterion of "attracting student participation by the master" has the next important place as well. The subcategory of the need for learning, the interest of  the interfere in education, and the future prospects of the student future are in the subsequent degree of importance.en_US
dc.format.extent1443
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoen_US
dc.publisherIranian Institute of Industrial Engineeringen_US
dc.relation.ispartofJournal of Industrial and Systems Engineeringen_US
dc.subjectPerformance measurementen_US
dc.subjectUncertaintyen_US
dc.subjectmulti criteria decision making (MCDM)en_US
dc.subjectE-learningen_US
dc.subjectanalytical network process (ANP)en_US
dc.subjectDecision Analysisen_US
dc.subjectPerformance Measurementen_US
dc.titleFuzzy analytical network process logic for performance measurement system of e-learning centers of universitiesen_US
dc.typeTexten_US
dc.typeResearch Paperen_US
dc.contributor.departmentSchool of Industrial Engineering, Iran University of Science and Technology, Tehran, Iranen_US
dc.contributor.departmentSchool of Industrial Engineering, Iran University of Science and Technology, Tehran, Iranen_US
dc.contributor.departmentSchool of Industrial Engineering, Iran University of Science and Technology, Tehran, Iranen_US
dc.citation.volume11
dc.citation.issue3
dc.citation.spage261
dc.citation.epage280


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