Title
SIERA: Visual analytics for multi-dimensional data for learning assessment in educational organisations
Date Issued
01 January 2016
Access level
metadata only access
Resource Type
conference paper
Publisher(s)
Springer Verlag
Abstract
Nowadays, data is produced at an incredible rate and the strategy to collect and store is increasing as faster as the strategy to analyse it. The correct analysis of these multidimensional data is very important for decision makers. Some Educational Organisations have a culture of evaluating the student’s knowledge, it makes possible to promptly discover weaknesses in the teaching and learning process. This paper describes a proposed strategy to collect multi-dimensional data and visual analytics for assessment that supports the evaluation process of educational organisations. To validate this proposal we used focus group. The proposed strategy was tested with 2677 schools and 160529 students in evaluation process in Apurimac-Peru. The test results show that teachers agree with the proposed strategy.
Start page
283
End page
287
Volume
9929 LNCS
Language
English
OCDE Knowledge area
Ciencias de la información
Ciencias de la computación
Ciencias de la educación
Subjects
Scopus EID
2-s2.0-84994168924
Source
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Resource of which it is part
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN of the container
03029743
ISBN of the container
9783319467702
Conference
13th International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2016 Sydney 24 October 2016 through 27 October 2016
Sponsor(s)
The authors are grateful to the REEDF/CEEP programs of the CECS (UM-D), the Rackham Faculty Grant (UM-AA), and the Office for Research and Sponsored Programs (UM-D) for supporting this work. The donation of Curv from Propex Fabrics Inc., USA, Twintex from Saint Gobain, USA, and XAF from Collano Xiro, Switzerland, is also gratefully acknowledged.
Sources of information:
Directorio de Producción Científica
Scopus