An Ontology Driven Model for E-Learning in K-12 Education
Petek Askar (Hacettepe University, Turkey), Kagan Kalinyazgan (Yuce Schools, Turkey), Arif Altun (Hacettepe University, Turkey) and S. Serkan Pekince (Yuce Information Systems, Turkey)
Copyright: © 2008
This chapter introduces the development of a K-12 education ontology for e-learning environments. It presents design and implementation processes, followed by several recommendations for future directions for ontology development. E-learning environments incorporate the notion of semantic web based ontologies into their future directions. Semantic web uses ontologies to show the interconnectedness in a web environment. Ontologies are being developed in order to decrease the annotated amount of markup and increase the reliability of using computational (intelligent) agents. Within the concept of semantic mapping, domain ontology is at the core of intelligent e-learning systems. In order to achieve an ontology for K-12 education, the authors propse a domain-specific ontology PoleONTO (Personilized Ontological Learning Environment) with the emphasis on its development and incorporation into an e-learning environment.
Key Terms in this Chapter
Implicit semantics: The kind that is implicit from the patterns in data and that is not represented explicitly in any strict machine processable syntax.
Powerful (soft) Semantics: The use of statistical analysis of data in order to explore the relationships that are not explicitly stated.
Ontology: An ontology is a controlled vocabulary that describes objects and the relations between them in a formal way, and has a grammar for using the vocabulary terms to express something meaningful within a specified domain of interest.
Learning Object: A chunk of elements that can be independently drawn into a momentary assembly in order to create an instructional expectation. These chunks can be reused, re- created and maintained, re-organized and stuck together.
Skill: The interaction and any processes between persons and concepts.
Formal semantics: The use of natural language as a means for machines to communicate with other machines by using machine-processable models and expressions.
Concept: The solid knowledge articulated across the curriculum.