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Evaluating Students Satisfaction in Online Postgraduate Courses Through a Fuzzy Linguistic Approach

Evaluating Students Satisfaction in Online Postgraduate Courses Through a Fuzzy Linguistic Approach

Yeleny Zulueta-Veliz, Aylin Estrada-Velazco, Yoisbel Tabares-Leon
Copyright: © 2022 |Volume: 18 |Issue: 1 |Pages: 25
ISSN: 1548-3673|EISSN: 1548-3681|EISBN13: 9781799893868|DOI: 10.4018/IJeC.304380
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MLA

Zulueta-Veliz, Yeleny, et al. "Evaluating Students Satisfaction in Online Postgraduate Courses Through a Fuzzy Linguistic Approach." IJEC vol.18, no.1 2022: pp.1-25. http://doi.org/10.4018/IJeC.304380

APA

Zulueta-Veliz, Y., Estrada-Velazco, A., & Tabares-Leon, Y. (2022). Evaluating Students Satisfaction in Online Postgraduate Courses Through a Fuzzy Linguistic Approach. International Journal of e-Collaboration (IJeC), 18(1), 1-25. http://doi.org/10.4018/IJeC.304380

Chicago

Zulueta-Veliz, Yeleny, Aylin Estrada-Velazco, and Yoisbel Tabares-Leon. "Evaluating Students Satisfaction in Online Postgraduate Courses Through a Fuzzy Linguistic Approach," International Journal of e-Collaboration (IJeC) 18, no.1: 1-25. http://doi.org/10.4018/IJeC.304380

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Abstract

Student satisfaction provides a students' perception of their educational experiences in an educational setting. As online learning is growing, institutions and instructors have become more interested in knowing what factors influence students' satisfaction in online learning setting. This study presents a novel approach for evaluating students' satisfaction in online postgraduate courses through a fuzzy linguistic approach for computing with words which addresses. Our approach models the students' satisfaction as a linguistic variable which reflects the perceptual nature of this concept; it models the satisfaction evaluation as a linguistic multi-attribute decision-making problem; it gathers perceptions of students according to 14 attributes for 18 online courses; it offers a methodological framework based on the 2-tuple linguistic model for computing with words through which performs a linguistic multi-step incremental aggregation process that outputs at each step partial or global self-contained and informative results expressed in a common linguistic domain.

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