19 research outputs found
Analyzing the determinant characteristics for a good performance at enade brazilian exam stratified by teaching modality: face-to-face versus online
The National Student Performance Exam (ENADE) annually evaluates different Brazilian higher education courses. This exam considers both face-to-face and distance learning courses. Distance learning is growing increasingly, especially during the coronavirus (COVID-19) pandemic. This study applies different techniques for selecting ENADE 2018 database characteristics, like information gain, gain rate, symmetric uncertainty, Pearson correlation, and relief F. The objective of the work is to discover which personal and socioeconomic characteristics are decisive for the student's performance at ENADE, whether the student is in the context of Distance Education or face-to-face. It can be concluded, among other results, that: the father's level of education directly influences performance; the higher the income, the better the performance; and white students have better performance than black and brown-skinned ones. Thus, the results obtained in this study may initiate analyzes of public policies towards improving performance at ENADE.This study was supported by CNPq (305805/2021-5) and PNPD/CAPES (464880/2019-00)
Constructing interval-valued fuzzy material implication functions derived from general interval-valued grouping functions
Grouping functions and their dual counterpart,
overlap functions, have drawn the attention of many authors,
mainly because they constitute a richer class of operators compared to other types of aggregation functions. Grouping functions
are a useful theoretical tool to be applied in various problems, like
decision making based on fuzzy preference relations. In pairwise
comparisons, for instance, those functions allow one to convey
the measure of the amount of evidence in favor of either of two
given alternatives. Recently, some generalizations of grouping
functions were proposed, such as (i) the n-dimensional grouping
functions and the more flexible general grouping functions, which
allowed their application in n-dimensional problems, and (ii)
n-dimensional and general interval-valued grouping functions,
in order to handle uncertainty on the definition of the membership functions in real-life problems. Taking into account
the importance of interval-valued fuzzy implication functions in
several application problems under uncertainty, such as fuzzy
inference mechanisms, this paper aims at introducing a new
class of interval-valued fuzzy material implication functions. We
study their properties, characterizations, construction methods
and provide examples.upported by CNPq (301618/2019-4, 311429/2020-3), FAPERGS (19/2551-0001660-3), UFERSA, the Spanish Ministry of Science and Technology (TIN2016-77356-P, PID2019-108392GB I00 (MCIN/AEI/10.13039/501100011033)) and Navarra de Servicios y Tecnologías, S.A. (NASERTIC)