CFP last date
20 June 2024
Reseach Article

Learner’s Performance Evaluation based on Knowledge Extracting and Ontology

by Sami A. M. Al-radaei, R. B. Mishra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 3
Year of Publication: 2012
Authors: Sami A. M. Al-radaei, R. B. Mishra

Sami A. M. Al-radaei, R. B. Mishra . Learner’s Performance Evaluation based on Knowledge Extracting and Ontology. International Journal of Computer Applications. 54, 3 ( September 2012), 24-29. DOI=10.5120/8546-2103

@article{ 10.5120/8546-2103,
author = { Sami A. M. Al-radaei, R. B. Mishra },
title = { Learner’s Performance Evaluation based on Knowledge Extracting and Ontology },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 3 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 24-29 },
numpages = {9},
url = { },
doi = { 10.5120/8546-2103 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T20:54:44.996312+05:30
%A Sami A. M. Al-radaei
%A R. B. Mishra
%T Learner’s Performance Evaluation based on Knowledge Extracting and Ontology
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 3
%P 24-29
%D 2012
%I Foundation of Computer Science (FCS), NY, USA

Test is one of the tools that are used to evaluate learner's achievement. Most of test scoring in e-learning systems are for true-false and fill in blank questions. Description questions are human efforts and time consuming. A courseware with its questions bank had been built based on ontology. Extracting the semantic keywords from the learner's answer would be used to score the answer. In this paper we introduce a method to score the learner's answer based on semantic keywords in the question's ontology. Position priority and frequency of occurrence the semantic keywords have been taken in our calculation. This scoring is used to evaluate the learner's performance to answer description questions.

  1. K. Mishra and R. B. Mishra, "Heuristic method for performance evaluation of learning in intelligent tutoring system " INFOCOM journal of computer science, vol. 9, pp. 1-7, 2010.
  2. T. Beleche, D. Fairris, and M. Marks, "Do course evaluations truly reflect student learning? Evidence from an objectively graded post-test," Economics of Education Review, vol. 31, pp. 709-719, 2012.
  3. C. -K. Chiou, G. -J. Hwang, and J. C. R. Tseng, "An auto-scoring mechanism for evaluating problem-solving ability in a web-based learning environment," Computers & Education, vol. 53, pp. 261-272, 2009.
  4. W. Han, X. Jun, Feng, and Gang, "Implementation of A Testing System on Web-based Course of C Programming Language," J. Computer & Digital Engineering, vol. 31, pp. 37-41, 2003.
  5. M. R. Del Sorbo and W. Balzano, "e-Xamina: An Experimental Multi-user Assessment Platform for Computer Adaptive Testing," 2011, pp. 237-240.
  6. A. Bentiba, M. J. Zemerly, O. A. Hammadi, S. A. Sharif, and M. Naqbi, "Dynamic Generated Material for E-Learners (DGML)," 2011, pp. 247-250.
  7. F. Yang and G. Liu, "Study and application of automatic scoring technology in C programming test," 2012, pp. 587-589.
  8. D. S. Morris, "Automatic grading of student's programming assignments: an interactive process and suite of programs," 2003, pp. S3F - 1-6 vol. 3-S3F - 1-6 vol. 3.
  9. A. Gladun, J. Rogushina, Garc, F. a-Sanchez, Mart, B. nez, R. jar, Fern, and J. T. ndez-Breis, "An application of intelligent techniques and semantic web technologies in e-learning environments," Expert Syst. Appl. , vol. 36, pp. 1922-1931, 2009.
  10. E. Kontopoulos, D. Vrakas, F. Kokkoras, N. Bassiliades, and I. Vlahavas, "An ontology-based planning system for e-course generation," Expert Systems with Applications, vol. 35, pp. 398-406, 2008.
  11. C. -M. Chen, C. -J. Peng, and J. -Y. Shiue, "Ontology-based concept map for planning personalized learning path," 2008, pp. 1337-1342.
  12. J. Emina, "Preparation of the learning content for semantic e-learning environment," Procedia - Social and Behavioral Sciences, vol. 1, pp. 824-828, 2009.
  13. C. -C. Tsai, "Taiwanese Science Students' and Teachers' Perceptions of the Laboratory Learning Environments: Exploring Epistemological Gaps," International Journal of Science Education, vol. 25, pp. 847-60, 2003.
  14. H. -L. Yang and M. -H. Ying, "Scoring Effect of Online Test: Implications on KM and e-learning," INTERNATIONAL JOURNAL OF INNOVATION AND LEARNING, vol. 4, pp. 40--58-40--58, 2007.
  15. T. Berners-Lee, J. Hendler, and O. Lassila. (2001, May 2001) The Semantic Web. Scientific American
  16. S. A. M. Al-Radaei and R. B. Mishra, "A Heuristic Method for Learning Path Sequencing for Intelligent Tutoring System (ITS) in E-learning," International Journal of Intelligent Information Technologies, vol. 7, pp. 65-80, 2011.
  17. R. B. Mishra and S. Kumar, "Semantic web reasoners and languages," Artif. Intell. Rev. , vol. 35, pp. 339-368, 2011.
  18. A. Kalyanpur, B. Parsia, and J. Hendler, "A Tool for Working with Web Ontologies," International Journal on Semantic Web and Information Systems, vol. 1, pp. 36-49, 2005.
  19. E. Prud and A. Seaborne. (2008). SPARQL Query Language for RDF. Available: http://www. w3. org/TR/rdf-sparql-query/
Index Terms

Computer Science
Information Sciences


E-learning Semantickeywords Ontology