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Evaluating intertwined effects in e-learning programs: A novel hybrid MCDM model based on factor analysis and DEMATEL

机译:评估在线学习程序中的相互影响:基于因子分析和DEMATEL的新型混合MCDM模型

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摘要

Internet evolution has affected all industrial and commercial activity and accelerated e-learning growth. Due to cost, time, or flexibility for designer courses and learners, e-learning has been adopted by corporations as an alternative training method. E-learning effectiveness evaluation is vital, and evaluation criteria are diverse. A large effort has been made regarding e-learning effectiveness evaluation; however, a generalized quantitative evaluation model, which considers both the interaffected relation between criteria and the fuzziness of subjective perception concurrently, is lacking. In this paper, the proposed new novel hybrid MCDM model addresses the independent relations of evaluation criteria with the aid of factor analysis and the dependent relations of evaluation criteria with the aid of DEMATEL. The AHP and the fuzzy integral methods are used for synthetic utility in accordance with subjective perception environment. Empirical experimental results show the proposed model is capable of producing effective evaluation of e-learning programs with adequate criteria that fit with respondent's perception patterns, especially when the evaluation criteria are numerous and intertwined.
机译:互联网的发展已影响到所有工业和商业活动,并加速了电子学习的增长。由于设计课程和学习者的成本,时间或灵活性,公司已采用电子学习作为替代培训方法。电子学习效果评估至关重要,评估标准也多种多样。在电子学习效果评估方面已经做出了巨大努力;但是,缺乏同时考虑标准之间的相互影响关系和主观感知的模糊性的广义量化评估模型。在本文中,提出的新型新型混合MCDM模型借助因子分析解决了评估标准的独立关系,并借助DEMATEL解决了评估标准的依赖关系。根据主观感知环境,将层次分析法和模糊积分法用于综合效用。实验结果表明,所提出的模型能够以符合受访者感知模式的适当标准对在线学习计划进行有效评估,尤其是当评估标准众多且相互交织时。

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