Capturing Uncertainty in Opinions on Distance Learning Using Fuzzy Sets

ABSTRACT

Due to the COVID-19 pandemic, distance learning has become a hot topic in education. Universities worldwide were forced to replace traditional learning with distance learning without deeper preparation. The focus was mostly put on technical solutions. However, the opinions and feelings of the groups involved - mainly teachers, students, and IT staff, should be also considered. Given the novelty of the situation, it is unreasonable to expect that the collected answers are without vagueness and hesitance. To solve this problem, this work proposes a method of capturing and aggregating such answers. At the first level, the answers of a single respondent are represented as fuzzy numbers whose mean is then calculated to represent their overall opinion. At the second level, the aggregation by the relative quantifier most of reveals whether the majority of members of a group inclines towards a positive or negative opinion. In this way, the uncertainties in answers and non-equal sizes of groups are covered. This model is illustrated by a numerical example followed by discussion and concluding remarks. © Proceedings of the 14th International Conference on Strategic Management and its Support by Information Systems 2021, SMSIS 2021.