Applied Picture Fuzzy Sets for Group Decision-Support in the Evaluation of Pedagogic Systems

ABSTRACT

Evaluation of E-Learning resources plays a significant role in the context of pedagogic systems. Resource evaluation is important in both conventional 'talk-and-chalk' teaching and in blended learning. In on-line (e-learning) teaching [an enforced feature of pedagogic systems in tertiary education during the Covid-19 pandemic] the effective evaluation of teaching resources has obtained importance given the lack of 'face-to-face' student-teached interaction. Moreover, the enforced use of e-learning has demonstrated the effectiveness of on-line pedagogic systems, which has been argued in blended learning pedagogic systems. Additionally, in e-learning, the lack of 'face-to-face' meetings [between teaching staff and students and in staff meetings] makes feedback (positive and negative) important for all actors in the pedagogic system. In this paper we present a novel approach to enable effective evaluation of teaching resources, which provides effective group decision-support designed to evaluate e-learning resources, enhancing students' satisfaction. The proposed approach employs Picture Fuzzy Sets to quantify survey responses from actors, including agree, disagree, neutral, and refuse to answer. In our approach, the system can manage the evaluation of e-learning resources based on both explicit and tacit knowledge using a picture fuzzy rule-based approach in which linguistic semantic terms are used to express rules and preferences. The proposed system has been tested using e-learning case studies with the goal of enhancing the learning experience and increasing students' satisfaction. Experimental results demonstrate that our proposed approach achieves a significant improvement in performance in the evaluation of e-learning resources.