KNOWLEDGE ENGINEERING METHODS IN DISTRIBUTED EDUCATIONAL CONTENT DESIGN
https://doi.org/10.21686/1818-4243-2015-4(111-51-57
Abstract
Educational content is considered by authors as a distributed system of learning objects, that are self-contained, interoperable, and reusable in multiple contexts. Phases of educational content design, based on ontology engineering methods, are described: knowledge identification, knowledge conceptualization, knowledge categorization, knowledge formalization, and knowledge implementation.
About the Authors
Galina N. BoychenkoRussian Federation
the Department of theory and methodology of teaching computer science
Candidate of Pedagogical Sciences, docent, assistant professor
Tel.: 7 9050782797
Liudmila I. Kundozzerova
Russian Federation
the Department of Penitentiary Psychology and Penitentiary Pedagogy
Doctor of Education, professor, professor,
Tel.: +7 960 913-25-00
References
1. Краевский В.В., Бережнова Е.В. Методология педагогики: новый этап / 2-е изд., стер. – М: Академия, 2008. – 393 с.
2. Hutchins E. Distributed cognition. In: The International Encyclopedia of the Social and Behavioral Sciences, pp 2068–2072, 2001.
3. Hutchins E. Cognitive artifacts // The MIT Encyclopedia of the Cognitive Sciences, R.A. Wilson & F.C. Keil (eds), Cambridge, MA: The MIT Press. – 1999. P. 126–128.
4. The Instructional Use of Learning Objects. Edited by David A. Wiley. Agency for Instructional Technology and the Association for Educational Communications and Technology. 2002. 298 p. ISBN: 0-7842-0892-1. Online version is available at http://reusability.org/ read/
5. 1484.12.1-2002 IEEE Standard for Learning Object Metadata. Final draft standard. 15 July 2002. URL: http://ltsc.ieee.org/wg12/files/LOM_1484_12_1_v1_ Final_Draft.pdf
6. Gruber T.R. Toward Principles for the Design of Ontologies Used for Knowledge Sharing // International Journal Human-Computer Studies. – 1995. – Vol. 43(5–6). – P. 907–928.
7. Dr. Tom Gruber’ s (Co-founder and Chief Technical Officer of Intraspect Software) Interview For the Official Quarterly Bulletin of AIS Special Interest Group on Semantic Web and Information Systems. – 2004. – Vol. 1, Issue 3. URL: http://tomgruber.org/ writing/sigsemis-2004.pdf
8. Gavrilova T., Leshcheva I., Rumyantseva M. Knowledge Elicitation Methods Taxonomy: Russian view // Knowledge-Based and Intelligent Information and Engineering Systems, Lecture Notes in Computer Science. Springer. – 2011. – Vol. 6881/2011. – P. 337–346.
9. Cohen H., Lefebvre, C. Handbook of Categorization in cognitive science. Amsterdam: Elsevier Science, 2005. – 1136 p.
10. Rosch E. Prototype classification and logical classification: The two systems // E.F.Scholnick (Ed.), New trends in conceptual representation: Challenges to Piaget’s theory? – Hillsdale, NJ: Erlbaum, 1983. – P. 73–86.
11. Protégé. A free, open-source ontology editor and framework for building intelligent systems. Official site. URL: http://protege.stanford.edu/
12. Reigeluth C.M., Merrill M.D. Bunderson C.V. The structure of subject matter content and its instructional design implications // Instructional Science, 1978. – Vol. 7(2). – P. 107–126.
Review
For citations:
Boychenko G.N., Kundozzerova L.I. KNOWLEDGE ENGINEERING METHODS IN DISTRIBUTED EDUCATIONAL CONTENT DESIGN. Open Education. 2015;(4(111):51-57. (In Russ.) https://doi.org/10.21686/1818-4243-2015-4(111-51-57