Visualizing Knowledge Awareness Support in Ubiquitous Learning

2011 ◽  
pp. 15-29 ◽  
Author(s):  
Moushir M. El-Bishouty ◽  
Hiroaki Ogata ◽  
Yoneo Yano
Keyword(s):  
Learning Environment ◽  
Ubiquitous Learning ◽  
Educational Materials ◽  
Environmental Objects ◽  
Current Location ◽  
Peer Helpers ◽  
Awareness Support ◽  
Ubiquitous Learning Environment

The aim of this research is to provide the learner with knowledge awareness support according to his current need and location. Therefore, we presented a ubiquitous learning environment in order to support the learners while doing tasks; this environment is called PERKAM (PERsonalized Knowledge Awareness Map). PERKAM allows the learners to share knowledge, interact, collaborate, and to exchange individual experiences. It utilizes ubiquitous technologies to detect the learner’s environmental objects and location, and then recommends the best matched educational materials and peer helpers in accordance with the detected objects and the current location. This environment provides the learner with Knowledge Awareness Map, which graphically displays the knowledge awareness support. The experiment and the questionnaire results indicated that Knowledge Awareness Map is helpful to understand the learner’s situation and it efficiently visualizes the recommendations.

scholarly journals Automatic, global and dynamic student modeling in a ubiquitous learning environment

2009 ◽  
pp. 18-35
Keyword(s):  
Learning Environment ◽  
Learning Styles ◽  
Student Modeling ◽  
Learning Material ◽  
Ubiquitous Learning ◽  
Student Model ◽  
Current Location ◽  
Level Problem ◽  
The Right ◽  
Ubiquitous Learning Environment

Ubiquitous learning allows students to learn at any time and any place. Adaptivity plays an important role in ubiquitous learning, aiming at providing students with adaptive and personalized learning material, activities, and information at the right place and the right time. However, for providing rich adaptivity, the student model needs to be able to gather a variety of information about the students. In this paper, an automatic, global, and dynamic student modeling approach is introduced, which aims at identifying and frequently updating information about students’ progress, learning styles, interests and knowledge level, problem solving abilities, preferences for using the system, social connectivity, and current location. This information is gathered in an automatic way, using students’ behavior and actions in different learning situations provided by different components/services of the ubiquitous learning environment. By providing a comprehensive student model, students can be supported by rich adaptivity in every component/service of the learning environment. Furthermore, the information in the student model can help in giving teachers a better understanding about the students’ learning process.

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