A Study of Relation Cateogry for LOM - Using E-Learning in Information Technology as an Example

• Main Authors: Chin-Ju Hsieh, 謝謹如
• Other Authors: Eric Jui-Lin Lu
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/50705447379666526305

碩士 === 朝陽科技大學 === 資訊管理系碩士班 === 95 === The development of e-learning related technologies has become an important research area. One of the major challenges in e-learning research is how to define and extract appropriate relationships between Learning Objects(LOs). The explicit relationships can improve the interchangeability and usability of LOs. As a result, IEEE developed a standard called LOM (Learning Object Metadata) to express the relationships between LOs. However, the recommended relations in LOM cannot precisely express semantic relationships between LOs. For example, there are two LOs: one is LO_A which describes a definition bubble sort, and another is LO_B which is an example of bubble sort. By using the relations defined in LOM, we can only express a "REFERENCE" relation between them. It will be much better if we can define a relation, say EXAMPLE, then we can define that LO_B is an "EXAMPLE" of LO_A. To resolve the problem, two major approaches were developed. One approach is based on the Instructional Design Theory (IDT)[7] and the other approach is based on the Rhetorical Structure Theory (RST) [6]. Based on the IDT, searchers [10, 23.24.25] classified relationships between LOs into Fundamental relations that describe the relationship between LOs and learning topic ,and Auxiliary relations that express the relationship between LOs. The RST is used to express potential rhetoircal relationship between LOs [8, 11, 17, 18, 19, 20]. Although many relations have been defined, it is found that the proposed relations overlap and inappropriate problems.In addition, theses proposed relations were not tested and verified in the past researches. Therefore, In this paper, we summarized and analyzed existing relations, removed duplicated relations, and developed a relation ontology. In the relations test and verify, We use the questionnaire to understand these relations that defined in relation ontology can increase the learning effect of learners. As a result, most of relations in relation ontology really can increase the learner''s effect of e-learning, and therefore these relations can increase usability and interoperability of LOs and achieve the objective of SCORM. In addition, the tester of learners can divided into college students and graduate students and We also detect some relation effect of the learners in different group are different between each other. For this reason, it will much better to design exclusive LMs for different group of learners can increase the effect of e-learning. In the further research, we will implement an author system and try to understand these relations can extend usability and interoperability of LOs by teachers view ,and reduce the time, cost and difficulity of LMs authoring.