Title :
Multilinear Educational Data Analysis for Evaluation of Engineering Education
Author :
Vasconcelos, F.H.L. ; Silva, T.E.V. ; Mota, J.C.M.
Author_Institution :
Univ. Fed. do Ceara, Fortaleza, Brazil
Abstract :
In this paper, we present a research study of educational evaluation in an engineering undergraduate degree. A multilinear decomposition, called Parallel Factors Analysis (PARAFAC), was used to extract intrinsic information about twokinds of evaluation: Learning Outcomes (LO) and Learning Context (LC). The results obtained allow us to identify common characteristics and similarities in disciplines in the undergraduate degree curriculum, both in terms of students´ opinion and students´ performance. The PARAFAC model also demonstrated significant potential for extracting data information related latent variables in educational contexts considering the sample multidimensionality.
Keywords :
engineering education; further education; learning (artificial intelligence); PARAFAC model; engineering education evaluation; learning context; learning outcome; multilinear decomposition; multilinear educational data analysis; parallel factor analysis; undergraduate degree curriculum; Analytical models; Atmospheric modeling; Context; Data mining; Gold; Principal component analysis; Tensile stress; Educational Evaluation; Learning Context; Learning Outcomes; Multilinear Analysis; PARAFAC;
Journal_Title :
Latin America Transactions, IEEE (Revista IEEE America Latina)
DOI :
10.1109/TLA.2015.7332163
