Research on Fuzzy Linguistic Evaluation in e-Learning Using AHP and TOPSIS Based on Web Resources

This study proposes a holistic approach for determining critical attributes in e-learning measurements. There is an abundance of literature pertaining to the e-learning framework, but there is a shortage of literature on how to properly implement the framework in uncertainty with variance and interactive relationships. This paper also considers the nature of fuzziness in human perception and avoids the erroneous assumptions of conventional analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), proposing a hybrid approach. AHP is employed to weight the criteria in an objective way. Then, TOPSIS is applied to rank the alternatives for this evaluation. In order using the fuzzy theory to represent customer perception based on linguistic assessment aspects in uncertainty. The 4 dependence aspects and 25 interactive criteria were evaluated from a sample of fifteen respondents. The results and concluding remarks are discussed.