Title :
Quality metrics a quanta for retrieving learning object by clustering techniques
Author :
Sabitha, A.S. ; Mehrotra, Deepti ; Bansal, Ankur
Author_Institution :
Dept. of CS &IT, Krishna Eng. Coll., Ghaziabad, India
Abstract :
E-learning today has shown exponential growth as it provides the potential to provide right information to the right people at right time and place, using the right medium. The atomic unit of any e-learning environment is a Learning object, a digital entity which can be used in electronic learning environment. These learning objects are stored in repositories and are managed by Learning Management Systems. However, the exponential availability of information leads to a difficult scenario like finding a particular educational resource for a learner, based on the context or based on his/her preferences. The searching through keywords or metadata will result in display of huge quantity of information. Thus there is an earnest need to identify the techniques that can provide more efficient mechanism for information retrieval. In this paper a model is being proposed that can enhance the search and delivery of a relevant learning object to a learner using quality metrics & clustering of learning objects through Self Organising Maps.
Keywords :
information retrieval; pattern clustering; E-learning today; clustering technique; electronic learning environment; information retrieval; learning management system; learning object retrieving; particular educational resource; quality metrics; self organising maps; Algorithm design and analysis; Clustering algorithms; Data mining; Electronic learning; Least squares approximation; Measurement; Search problems; Clustering; K-mean; Learning Objects (LO); Quality Metrics; Recommender System; Self Organizing Map;
Conference_Titel :
Digital Information and Communication Technology and it's Applications (DICTAP), 2012 Second International Conference on
Conference_Location :
Bangkok
Print_ISBN :
978-1-4673-0733-8
DOI :
10.1109/DICTAP.2012.6215396