An approach to automatic learning assessment based on the computational theory of perceptions

Sanchez Torrubia, Maria Gloria and Torres Blanc, Carmen and Triviño Barros, Gracián (2012). An approach to automatic learning assessment based on the computational theory of perceptions. "Expert Systems with Applications", v. 39 (n. 15); pp. 12177-12191. ISSN 0957-4174. https://doi.org/10.1016/j.eswa.2012.04.069.

Description

Title: An approach to automatic learning assessment based on the computational theory of perceptions
Author/s:
  • Sanchez Torrubia, Maria Gloria
  • Torres Blanc, Carmen
  • Triviño Barros, Gracián
Item Type: Article
Título de Revista/Publicación: Expert Systems with Applications
Date: 1 November 2012
Volume: 39
Subjects:
Freetext Keywords: Automatic learning assessment, Computing with words and perceptions, Granular linguistic model of a phenomenon, Evaluación del aprendizaje automática, Informática con palabras y percepciones, Modelo lingüístico y granular de un fenómeno.
Faculty: Facultad de Informática (UPM)
Department: Matemática Aplicada
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview

Abstract

E-learning systems output a huge quantity of data on a learning process. However, it takes a lot of specialist human resources to manually process these data and generate an assessment report. Additionally, for formative assessment, the report should state the attainment level of the learning goals defined by the instructor. This paper describes the use of the granular linguistic model of a phenomenon (GLMP) to model the assessment of the learning process and implement the automated generation of an assessment report. GLMP is based on fuzzy logic and the computational theory of perceptions. This technique is useful for implementing complex assessment criteria using inference systems based on linguistic rules. Apart from the grade, the model also generates a detailed natural language progress report on the achieved proficiency level, based exclusively on the objective data gathered from correct and incorrect responses. This is illustrated by applying the model to the assessment of Dijkstra’s algorithm learning using a visual simulation-based graph algorithm learning environment, called GRAPHs

More information

Item ID: 15804
DC Identifier: http://oa.upm.es/15804/
OAI Identifier: oai:oa.upm.es:15804
DOI: 10.1016/j.eswa.2012.04.069
Official URL: http://www.elsevier.com/locate/eswa
Deposited by: Memoria Investigacion
Deposited on: 17 Jun 2013 16:57
Last Modified: 21 Apr 2016 16:06
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM