Multilinear Educational Data Analysis for Evaluation of Engineering Education

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 (L...

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Bibliographic Details
Published in:Revista IEEE América Latina 2015-08, Vol.13 (8), p.2785-2791
Main Authors: Lima Vasconcelos, Francisco Herbert, Veloso da Silva, Thomaz Edson, Moura Mota, Joao Cesar
Format: Article
Language:English
Subjects:
Analogies
Analytical models
Atmospheric modeling
Context
Data mining
Data processing
Decomposition
Education
Educational Evaluation
Factor analysis
Gold
Learning
Learning Context
Learning Outcomes
Mathematical models
Multilinear Analysis
PARAFAC
Principal component analysis
Students
Tensile stress
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Summary: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.
ISSN:1548-0992
1548-0992
DOI:10.1109/TLA.2015.7332163