International Journal of Mathematical, Engineering and Management Sciences (Apr 2022)

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

  • Hai Van Pham,
  • Nguyen Dang Khoa,
  • Thi Thuy Hang Bui,
  • Nguyen Thi Huong Giang,
  • Philip Moore

DOI
https://doi.org/10.33889/IJMEMS.2022.7.2.016
Journal volume & issue
Vol. 7, no. 2
pp. 243 – 257

Abstract

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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.

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