Towards Fuzzy Domain Ontology Based Concept Map Generation for E-Learning

Author(s):  
Raymond Y. K. Lau ◽  
Albert Y. K. Chung ◽  
Dawei Song ◽  
Qiang Huang
Author(s):  
Hussein Ali Ahmed Ghanim ◽  
László Kovács

<p>E-Learning is an important support mechanism for educational systems to increase the efficiency of the education process including students and teachers. The current e-learning systems typically lack the level of metacognitive awareness, adaptive tutoring, and time management skills and have not always met the expectations of the learners as required. In this study, we introduce a novel ontological model for the learning process in the e-learning domain. In the framework, we have built a domain ontology that represents knowledge of the learning, the outcome domain ontology covers the whole learning process. We focused on the learning process ontology model conceptualizing knowledge constructions, such as learning courses, and we present the created course and learning process ontology in detail. In this work, we considered three layers of learning process. The top layer defines a general framework of learning process, conceptual model layer, defines the framework of the actual process of the learning process and course ontology model contains the knowledge unit of the learning process. The prototype ontology is constructed in protégé and managed by Java web ontology language-application programming interface (OWL-API). As a result, our model can solve the problems of current e-tutor systems. Also, it can be used for different domain in e-tutor systems. It can reach the characteristics of standardization, reusability, flexibility, and open knowledge. By applying this model, we can avoid applying isolated databases. The constructed ontology can be used in the future to control adaptive intelligent e-tutor frameworks.</p>


Author(s):  
Christina J. Preston

This chapter focuses on teachers’ multidimensional concept mapping data collected at the beginning and end of a one-year Masters level course about e-learning. A multidimensional concept map (MDCM) defines any concept map that is multimodal, multimedia, multilayered and/or multi-authored. The teachers’ personal and professional learning priorities are analysed using two semiotic methods: the first is a traditional analysis of the words used to label the nodes; the second is an innovative analysis method that treats the whole map as a semiotic artefact, in which all the elements, including the words, have equal importance. The findings suggest that these tools offer deep insights into the learning priorities of individuals and groups, especially the affective and motivational factors. The teachers, as co-researchers, also adopted MDCM to underpin collaborative thinking. These research tools can be used in the assessment process to value multimodal literacy and collaborative engagement in new knowledge construction.


Author(s):  
Khalissa Derbal Amieur ◽  
Kamel Boukhalfa ◽  
Zaia Alimazighi

Geographic Information (GI) is currently available at any time, from anywhere on the surface of the earth, for any person connected to internet. Some applications of design, implementation, generation and dissemination of maps on the web are recognized as “Webmapping” application, geographic web services or more generally on demand-map making tools. All these web applications aims the satisfaction of user needs by providing personalized maps in a fast response time with a good quality. However, the complexity and diversity of aspects taking into account have lead researchers to focus on one aspect at the expense of others. Consequently, few works have addressed all these aspects simultaneously. The authors propose in this paper, a Webmapping approach organized into two main tasks: (1) query analysis driven by domain ontology in analyzing a query launched by a user on a web browser and (2) map generation process. The first step allows extracting and formalizing user needs through two map determinants factors: the Level of Detail (LoD) and Point of View (PoV) and the second, exploit an hybrid approach “Multi Representation and Generalization” in storing and generating geographical data with integrating Multi-Agent technology in all steps of processing. To evaluate the effectiveness of our proposal, a first tool prototype implementing our approach is so developed using a geographic vector dataset provided by national cartographic agency.


2011 ◽  
Vol 3 ◽  
pp. 524-529 ◽  
Author(s):  
Hendijanifard Fatemeh ◽  
Kardan Ahmad ◽  
Dibay Moghadam Mohammad

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