• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Mathematics, Statistics, and Their Applications >Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights
【24h】

Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

机译：使用TOPSIS技术选择合适的电子学习方法，具有最佳排名标准权重

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.
机译：本文比较了四个基于级别的加权评估技术的性能，等级和排名互惠（RR），排名指数（RE），以及第五个确定的电子学习标准的排名指数，以及排名定见程序，以选择最佳的电子学习标准权重方法。在马来西亚的公立大学共有35名专家们被要求对标准进行排名，并评估五种电子学习方法，包括混合学习，翻转课堂，ICT支持面对面学习，同步学习和异步学习。然后，最佳排名标准权重定义为具有所有重量的几何均值的总体绝对差异，然后使用Topsis方法选择最合适的电子学习方法。结果表明，RR权重是最好的，而翻转课堂方法实施是最合适的方法。本文制定了一个决定框架，以帮助决策者（DMS）选择最合适的加权方法来解决MCDM问题。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号