Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights
his 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 Mal...
محفوظ في:
| المؤلفون الرئيسيون: | , , |
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| التنسيق: | مقال |
| منشور في: |
IP Publishing LLC
2017
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://repo.uum.edu.my/24909/ http://doi.org/10.1063/1.5012207 |
| الوسوم: |
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| الملخص: | his 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. |
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