Title :
Yotta: A Knowledge Map Centric E-Learning System
Author :
Zheng, Qinghua ; Qian, Yanan ; Liu, Jun
Author_Institution :
MOE KLINNS Lab., Xi´´an Jiaotong Univ., Xi´´an, China
Abstract :
Current e-learning systems are primarily resource oriented, rather than cognition oriented. To reduce learners´ cognitive overload in e-learning, we proposed a novel e-learning system Yotta tackling the problem of knowledge acquisition, knowledge presentation, and knowledge resources management. The granularity for knowledge acquisition in Yotta is based on knowledge units that are the smallest integral learning objects in a specific domain. Knowledge presentation and navigation in Yotta is based on knowledge maps, which can exhibit knowledge and the intrinsic knowledge relations at both concept level and knowledge unit level. Automatic knowledge unit extraction and knowledge map construction techniques are also discussed in this paper. Yotta allows for huge concurrent access and enormous resource storage, as it is deployed on a cloud platform with the Hadoop distributed file system. The Yotta demo has already been implemented on our campus network, and has been approved by hundreds of students. Yotta offers new ideas for building e-learning systems, and its core techniques still require further study.
Keywords :
computer aided instruction; knowledge acquisition; knowledge management; Hadoop distributed file system; Yotta demo; automatic knowledge unit extraction; cloud platform; e-learning systems; integral learning objects; knowledge acquisition; knowledge map centric e-learning system; knowledge map construction; knowledge maps; knowledge navigation; knowledge presentation; knowledge relations; knowledge resources management; Electronic learning; Feature extraction; Knowledge acquisition; Navigation; Ontologies; Resource management; Hadoop DFS; cloud platform; e-learning; knowledge map; knowledge unit;
Conference_Titel :
e-Business Engineering (ICEBE), 2010 IEEE 7th International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-8386-0
Electronic_ISBN :
978-0-7695-4227-0
DOI :
10.1109/ICEBE.2010.43